Kindle
type: channel
description: PreferPub is a reputable international publisher that specializes in peer-reviewed academic works. All books will undergo a rigorous, blinded peer review by at least two academic professionals. Although PreferPub receives academic books directly for review and potential publication, it also facilitates the indexing of books from other publishers and sources, including Kindle, OpenAIRE, and others, if accepted through our peer review process. PreferPub is a prestigious international academic publisher dedicated to the dissemination of cutting-edge research and scholarly knowledge. Renowned for its commitment to excellence, PreferPub serves as a leading platform for the publication and indexing of high-quality academic books. With a rigorous peer-review process, PreferPub ensures that only the most impactful and original works make their way into its esteemed collection. By maintaining stringent academic standards, PreferPub guarantees the credibility and reliability of the research it publishes, fostering the advancement of knowledge across various disciplines. PreferPub's reach extends beyond its own publications. As a forward-thinking publisher, it actively supports the indexing of books from diverse sources, including renowned platforms like Kindle, OpenAIRE, and others. By embracing this collaborative approach, PreferPub acknowledges the value of knowledge generated from various channels and strives to provide a comprehensive collection of scholarly works to its readers. In addition to its commitment to academic excellence, PreferPub prioritizes accessibility and global outreach. Its publications are available in both digital and print formats, catering to the preferences and needs of researchers, scholars, and readers worldwide. By leveraging technology and innovation, PreferPub ensures that its publications are widely accessible, facilitating the exchange of ideas and fostering intellectual dialogue on a global scale. Researchers and authors who choose PreferPu…
publisher: Kindle
language: en
publication name: Kindle
copyright: Since making research freely available supports a greater global exchange of knowledge, PreferPub provides immediate open access to its published books under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (CC BY-NC 4.0). This license allows others to share, copy, and redistribute the material in any medium or format, as well as adapt, remix, transform, and build upon the material, as long as the use is non-commercial and appropriate credit is given to the original work.
items: AI for Holistic Medicine: Understanding Multi-Organ Interactions in Cancers
items: Academic Textbook: Mechanistic AI in Medicine: Discovery of Mechanisms and Origins of Diseases
items: AI for Self-Diagnosis, Self-Monitoring, and Personalized Medicine
items: Clinical Decision-Making Using Artificial Intelligence
items: Artificial Intelligence for Hard-to-Treat and Unknown-Origin Cancers
items: Role of Immunogenetics in the Etiology, Diagnosis, and Treatment of Diseases
items: Large Language Models and ChatGPT in Medical Sciences: Foundations, Capabilities, and Challenges
items: Application of AI in Research and Data Science
items: Explainable Artificial Intelligence for Reducing the Global Cancer Burden
items: Artificial Intelligence in Biomarker Discovery: Applications Across Medical Specialties
items: Intelligent Patient Engagement: Education and Follow-Up through AI and Telemedicine
items: AI in Medical Imaging and Early Disease Detection
items: Artificial Intelligence in Cancer Genomics: Transforming Diagnosis, Treatment, and Precision Medicine
items: The Future of Prosthetics and Organ Transplantation: A Therapeutic Approach Across Various Medical Disciplines
items: Artificial Intelligence in Genomic Medicine: Improving Diagnostic Accuracy and Treatment Outcomes
items: The Brain-Body Connection: Neuroscience’s Role Across Medical Sciences Disciplines
items: The AI Revolution: Predicting and Managing the Next Global Health Challenges and Emerging Disease Outbreaks
items: Robotics in Healthcare
items: Innovative Vaccination: A New Era in Cancer Prevention
items: AI-Driven Strategies for Improving Patient Quality of Life
items: Global Health Challenges
items: AI and Deep Learning in Understanding the Etiology and Pathogenesis of Autoimmune Diseases
items: Artificial Intelligence for Prediction of Metastasis Risk and Survival
items: AI-Enhanced Virtual Clinics and Telemedicine for Cancer Treatment
items: AI and Deep Learning in Understanding the Etiology and Pathogenesis of Cancers
items: AI Chatbots and Telemedicine in Cancer Care: Supporting Patients and Enhancing Communications
items: Complementary and Alternative Medicine (CAM)
items: Nanomedicine: Technologies and Applications
items: Digital Health and Wearable Technologies
items: The AI Diagnostician: Improving Medical Diagnosis with Artificial Intelligence

AI for Holistic Medicine: Understanding Multi-Organ Interactions in Cancers
type: item
description: Artificial intelligence (AI) is playing a major role in transforming holistic medicine, especially in cancer research and treatment. Traditionally, cancer was viewed as a disease that affects only one organ, such as the lungs, liver, or breast. However, recent scientific studies show that cancer is a complex disease involving interactions between multiple organs and biological systems. Tumors can influence the immune system, metabolism, hormones, blood circulation, and even distant organs through processes such as inflammation and metastasis. AI helps researchers and doctors understand these complicated connections more efficiently and accurately. One of the most important contributions of AI in holistic cancer medicine is its ability to analyze massive amounts of medical and biological data. Modern healthcare generates information from genomic sequencing, laboratory tests, medical imaging, electronic health records, and wearable devices. AI systems, particularly machine learning and deep learning models, can process this data to identify hidden patterns that humans may not easily detect. By combining information from different biological layers, known as “multi-omics” data, AI provides a more complete understanding of how cancer develops and spreads throughout the body. AI is also improving precision medicine, where treatments are tailored to the unique characteristics of each patient. Different patients often respond differently to the same cancer therapy. AI models can predict which treatments, such as chemotherapy, immunotherapy, or targeted drugs, are most likely to work for specific patients based on their genetic and molecular profiles. This personalized approach reduces unnecessary side effects and improves treatment outcomes. Another important application is AI-assisted medical imaging. AI-powered tools can analyze CT scans, MRI scans, and PET scans with high accuracy to detect tumors, monitor disease progression, and identify early signs of metastasis. The…
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Mehrdad Farrokhi
creator: Saman Abdollahpour
creator: Sanaz Amiri Marbini
creator: Niloofar Taheri
creator: Fatemeh Asadi
creator: Saboura Sahebi
creator: Oveis Ahmadzadeh
creator: Farzaneh Khosravi
creator: Kiana Bahmanipour
creator: Kimia Kowsari
creator: Atousa Ghorbani
creator: Rahil GhorbaniNia
creator: Nazanin Hashemi
creator: Khalil Kalavani
creator: Mohammad-Matin Karbalaee-Alinazari
creator: Meisam Sargazi
creator: Afshin Zarei
creator: Zahra Sadin
creator: Mahboobeh Majidnia
creator: Sara Shokrollahi Yancheshmeh
creator: Fatemeh Amini
creator: Vahid Jafari
creator: Atie Moghtadaei
creator: Sara Montazeri Namin
creator: Alireza Taheri
creator: Maryam Houshmand Marvasti
creator: Amin Sadeghnezhad
creator: Atena Talebpoor Amirhandeh
creator: Ali Aghajan
rights: Copyright (c) 2026 PreferPub and Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-12
publication date: 2026-05-12
starting page: 1
ending page: 186

Academic Textbook: Mechanistic AI in Medicine: Discovery of Mechanisms and Origins of Diseases
type: item
description: Mechanistic AI in medicine is revolutionizing the understanding of disease development and progression by shifting the focus from simple pattern recognition to the discovery of underlying biological mechanisms. Traditionally, identifying the causes and pathways of diseases has required extensive laboratory experimentation, clinical trials, and long-term observational studies. These approaches, although highly valuable, are often time-consuming, expensive, and limited by the complexity of biological systems. The emergence of artificial intelligence, particularly mechanistic AI, has introduced a transformative approach that accelerates biomedical research while offering deeper and more precise insights into human diseases. Unlike conventional AI systems that primarily rely on correlations within datasets, mechanistic AI seeks to understand causation. It integrates biological knowledge with computational modeling to explain how diseases originate, evolve, and affect the body at molecular, cellular, tissue, and systemic levels. By analyzing massive amounts of heterogeneous data such as genomic information, proteomics, electronic health records, laboratory findings, and medical imaging, mechanistic AI can uncover hidden interactions and pathways that may not be readily identifiable through traditional analytical methods. This capability enables researchers to move beyond symptom-based analysis toward a more comprehensive understanding of disease biology. One of the most important contributions of mechanistic AI is in genomics and precision medicine. Genetic mutations and variations often play a critical role in the onset of diseases such as cancer, cardiovascular disorders, and neurodegenerative conditions. Mechanistic AI models can simulate how these mutations alter protein structures, disrupt signaling pathways, or impair cellular functions. For example, in oncology, AI systems can identify how specific genetic abnormalities drive tumor growth and metastasis. Similarly…
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Neda Gorjizadeh
creator: Najmeh Tavousi
creator: Sina Talebi
creator: Masoumeh Moallem
creator: Mobina Gheibi
creator: Sadegh Bagherzadeh
creator: Leili Haghighi
creator: Mohammad Hossein Naderi
creator: Monireh Haghifar
creator: Kimia Kowsari
creator: Rojan Javaheri
creator: Mohammad Hossein Hosseiny
creator: Maedeh Masoumzadeh
creator: Shabnam Ghasemzaseh
creator: Massoma Rezai
creator: Behnaz Shirgir
creator: Asma Zamani
creator: Nasim Ghasemzadeh
creator: Meisam Sargazi
creator: AmirMohammad Larni-Fooeik
creator: Ali Azizi
creator: Saman Abdollahpour
creator: Sanaz Amiri Marbini
creator: Paniz Nejati
creator: AmirMasoud Karimi
creator: Zahra Khosravani Hasan Kiyadeh
rights: Copyright (c) 2026 PreferPub and Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-18
publication date: 2026-04-18
starting page: 1
ending page: 216

AI for Self-Diagnosis, Self-Monitoring, and Personalized Medicine
type: item
description: The integration of Artificial Intelligence into healthcare is fundamentally reshaping how we approach personal wellness, moving from reactive treatment to proactive, continuous self-management. AI algorithms, particularly those leveraging machine learning and deep learning, excel at processing vast, complex datasets, including genomic information, real time wearable sensor data, electronic health records, and lifestyle inputs, to derive insights far beyond human cognitive capacity. This capability empowers individuals with sophisticated self-diagnosis tools, often via conversational AI interfaces or analysis of uploaded medical imagery, offering preliminary risk assessments and identifying patterns indicative of specific conditions before symptoms become severe. Furthermore, AI drives continuous self-monitoring by creating intelligent digital health companions. These systems analyze streams of data from smartwatches or home diagnostics to track vital signs, sleep quality, and activity levels, flagging subtle deviations from an established baseline. This constant vigilance allows for immediate, personalized feedback, such as recommending a dietary change or suggesting a consultation, thereby enhancing adherence to health protocols. The ultimate promise lies in personalized medicine. By integrating individual biological profiles with population level data, AI can predict how a specific person will respond to different drugs or therapies. This moves healthcare away from one size fits all treatments toward highly tailored interventions, optimizing efficacy while minimizing adverse effects. This revolution promises a future where health management is deeply integrated, highly accurate, and uniquely tailored to the individual’s evolving biological needs, fostering unprecedented autonomy in one’s health journey.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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subject: Array
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creator: Mehrdad Farrokhi
creator: Ardeshir Zargar
creator: Behzad Paeizi
creator: Farzad Esfandyari
creator: Hamed Sabzehie
creator: Mina Ghazali
creator: Amirali Mohammadi
creator: Meisam Sargazi
creator: Reza Judi Chelan
creator: Amirreza Sabahizadeh
creator: Amirhossein Bahador
creator: Negareh Salehabadi
creator: Sanaz Amiri Marbini
creator: Saman Abdollahpour
creator: Parsa Farzan
creator: Mehdi Mohammadpour
creator: Zahra Tajik
creator: Horrieh Abbasmofrad
creator: Mitra Karami
creator: Hossein Boustani Hezarani
creator: Seyed Shahabedin Alemohammad
creator: Javaneh Atighi
creator: Peyman Alipoor
creator: Maryam Savardashtaki
creator: Mahya Naghipoor-Alamdari
creator: Farhad Shafiei
creator: Delaram Naderi
creator: Omid Fakharzadeh Moghadam
creator: Behnaz Shirgir
creator: Maryam Masoumzadeh
creator: Asma Sepahdar
creator: Khadijeh Harati
rights: Copyright (c) 2026 PreferPub and Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-29
publication date: 2026-05-29
starting page: 1
ending page: 226

Clinical Decision-Making Using Artificial Intelligence
type: item
description: Clinical decision-making using artificial intelligence represents a significant evolution in modern healthcare. Traditionally, clinical decisions have relied on physician experience, clinical guidelines, and manual interpretation of diagnostic data. As medical data have grown in volume and complexity, artificial intelligence has emerged as a valuable tool to support clinicians in synthesizing information and reducing uncertainty. Artificial intelligence systems analyze large and diverse datasets, including electronic health records, medical imaging, laboratory results, physiologic signals, and clinical text. Through machine learning and deep learning techniques, these systems identify patterns that may not be easily recognized by humans. This capability supports earlier diagnosis, more accurate risk stratification, and personalized treatment planning. In time sensitive settings, artificial intelligence can assist in prioritizing patients, predicting deterioration, and supporting rapid interventions. Importantly, artificial intelligence functions as a clinical decision support tool rather than a replacement for clinician judgment. Human oversight remains essential to interpret outputs, account for patient preferences, and manage ethical considerations. Well designed artificial intelligence systems are integrated into clinical workflows, providing recommendations that are transparent, interpretable, and actionable. Despite its promise, the use of artificial intelligence in clinical decision-making presents challenges. These include data quality, algorithmic bias, generalizability across populations, and concerns about privacy and accountability. Addressing these issues requires rigorous validation, ongoing monitoring, and clear governance frameworks. When implemented responsibly, artificial intelligence enhances clinical decision-making by improving consistency, efficiency, and precision. Its thoughtful integration has the potential to support clinicians, improve pati…
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Mehrdad Farrokhi
creator: Saba Mehrtabar
creator: Khadijeh Harati
creator: Tannaz Pourlak
creator: Erfan Ghadirzadeh
creator: Horrieh Abbasmofrad
creator: Reza Zahedpasha
creator: Peyman Bashghareh
creator: Kiana Bahmanipour
creator: Melika Hemmati
creator: Sepideh Amin Afshari
creator: Marjan Lashgari
creator: Masih Kavian
creator: Zahra Tajik
creator: Amirali Mohammadi
creator: Mohammad Mehdi Karimi Kenari
creator: Hamid Askari
creator: Ali Amiri
creator: Artin Rahimi
creator: Siavash Ketabi
creator: Kamyab Komaee Koma
creator: Kiana Nouri
creator: Reyhaneh Mehrvar
creator: Naeimeh Hosseini
creator: Javaneh Atighi
creator: Maryam Haghani
creator: Zahra Naseh
creator: Sheida Akhlaghitehrani
creator: Zohreh Kourehpaz Hassanalizad
creator: Roozbeh Roohinezhad
creator: Somayeh Hashemi Ali Abadi
creator: Seyed Amirali Zakavi
creator: Mahdi Javadian
creator: Mohammad Ali Daliri Ojghaz
creator: Mohammad Alinezhad Taheri
creator: Zahra Hamzehnejadi
creator: Eros Cribello
creator: Sayed Mohammadamin Tabatabaei
creator: Masoud Seifi
creator: Niloofar Taheri
creator: Omid Fakharzadeh Moghadam
creator: Sanaz Amiri Marbini
creator: Saman Abdollahpour
creator: Kameliya Sanjabiyan
rights: Copyright (c) 2025 PreferPub and Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-19
publication date: 2025-12-19
starting page: 1
ending page: 236

Artificial Intelligence for Hard-to-Treat and Unknown-Origin Cancers
type: item
description: Artificial intelligence is rapidly transforming the landscape of oncology, bringing new capabilities to the diagnosis and treatment of hard to treat and unknown origin cancers. These malignancies often present late, resist conventional therapy, and lack clear biological markers that guide personalized care. In cancers of unknown primary origin, clinicians struggle to determine where the disease began, making treatment decisions uncertain and less effective. Likewise, aggressive tumor types such as advanced sarcomas, rare gastrointestinal cancers, or refractory head and neck tumors often challenge standard medical approaches, leaving patients with limited options and poor prognoses. AI provides powerful tools to address these gaps by analyzing complex datasets with remarkable speed and precision. Machine learning models can evaluate radiologic scans, pathology slides, genomic sequencing, and clinical histories to detect patterns that escape human observation. Through these analytic strengths, AI can identify the most likely tissue of origin, predict therapeutic sensitivities, and assist in selecting targeted treatments that improve outcomes. Real time monitoring systems enhance patient management by detecting early signs of recurrence or treatment toxicity before they lead to irreversible harm. Furthermore, AI accelerates drug discovery and expands opportunities for innovative combination therapies. By modeling tumor evolution and resistance pathways, AI may help clinicians stay ahead of aggressive disease behavior. The overarching goal is to replace diagnostic uncertainty and treatment guesswork with data driven, personalized precision. As AI continues to mature, it holds significant promise to improve survival and quality of life for patients facing some of the most challenging cancer diagnoses in modern medicine.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Mehrdad Farrokhi
creator: Niloofar Taheri
creator: Omid Fakharzadeh Moghadam
creator: Mahdi Armoon
creator: Susan Samimi
creator: Narges Torkashvand
creator: Saeed Motevalli
creator: Shabahang Moghaddasi Esfivashi
creator: Elham Sadat Mostafavi
creator: Sepideh Hassanpour Khodaei
creator: Fatemeh Amini
creator: Zahra Taheri
creator: Sepide Javankiani
creator: Amir Nasrollahizadeh
creator: Reyhaneh Mahbubi Arani
creator: Oveis Ahmadzadeh
creator: Kimia Kowsari
creator: Kourosh Shahraki
creator: Mahyar Noorbakhsh
creator: Mohammad Bdaqli
creator: Roozbeh Roohinezhad
creator: Arezoo Heidary
creator: Kimia Baghebani
creator: Farzaneh Kianifar
creator: Reza Mohajer Shirazi
creator: Mohammad Eslami
creator: Shahram Asgari
creator: Yousef Fekri Dabanloo
creator: Saman Abdollahpour
creator: Sanaz Amiri Marbini
creator: Seyed Ali Hashemi Kiapey
creator: Atena Talebpoor Amirhandeh
creator: Mohammad Yaghoubi
creator: Neda Gorjizadeh
rights: Copyright (c) 2025 PreferPub and Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-05
publication date: 2025-12-05
starting page: 1
ending page: 296

Role of Immunogenetics in the Etiology, Diagnosis, and Treatment of Diseases
type: item
description: The role of immunogenetics in the etiology, diagnosis, and treatment of diseases has become increasingly prominent as advances in molecular biology and genomics have improved our understanding of host and pathogen interactions and the variability of the human immune system. Immunogenetics examines how genetic differences influence immune function, which in turn shapes individual susceptibility to infectious, autoimmune, inflammatory, and neoplastic conditions. Variants in genes that encode cytokines, human leukocyte antigens, pattern recognition receptors, and immune-regulatory molecules can alter the magnitude and quality of immune responses. These inherited differences contribute to variations in disease severity, clinical progression, and long-term outcomes among individuals. In clinical practice, immunogenetic markers have become important tools for improving diagnostic precision. HLA typing, cytokine gene polymorphism profiling, and the identification of genetic variants in innate and adaptive immune pathways provide opportunities to distinguish disease subtypes, predict complications, and refine prognostic assessments. These markers also assist in the early identification of individuals who are at increased risk of developing immune-mediated disorders. Therapeutically, immunogenetics supports the development of personalized medicine. Genetic insights help guide the selection of targeted immunotherapies, predict treatment response, and reduce the likelihood of adverse effects. Examples include tailoring biologic therapies for autoimmune diseases based on cytokine pathway polymorphisms, adjusting vaccine strategies according to HLA profiles, and improving cancer immunotherapy by incorporating tumor and host immune interaction signatures. Understanding immunogenetic determinants also contributes to the creation of new therapeutic agents designed to modulate specific immune pathways. Overall, immunogenetics provides a comprehensive framework that links genetic var…
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Sepideh Louia
creator: Omid Fakharzadeh Moghadam
creator: Reza Judi Chelan
creator: Niloofar Taheri
creator: Fatemeh Amini
creator: Somayyeh Ahmadi
creator: Oveis Ahmadzadeh
creator: SeyedAshkan Mirzadeh Ahari
creator: Mohammad Eslami
creator: Saman Abdollahpour
creator: Sanaz Amiri Marbini
creator: Atena Talebpoor Amirhandeh
creator: Amir Tahavvori
creator: Neda Gorjizadeh
rights: Copyright (c) 2025 PreferPub and Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2025-11-22
publication date: 2025-11-22
starting page: 1
ending page: 222

Large Language Models and ChatGPT in Medical Sciences: Foundations, Capabilities, and Challenges
type: item
description: Large Language Models (LLMs) such as ChatGPT have transformed how medical knowledge is accessed and used. Built on transformer-based deep learning architectures, these systems are trained on massive datasets containing biomedical and general language sources. This training enables them to interpret clinical text, summarize research findings, and generate coherent, contextually relevant responses. In medicine, LLMs now support a wide range of applications including literature screening, clinical documentation, education, and patient interaction. ChatGPT, in particular, can help synthesize evidence, draft research manuscripts, explain complex medical concepts, and assist in decision support when appropriately guided. These tools have accelerated many aspects of medical research and practice by improving efficiency and accessibility of information. Despite these advances, challenges remain significant. LLMs can produce inaccurate or fabricated information, known as hallucinations, which poses risks in clinical and research settings. Their training data may contain biases that influence outputs, and their decision-making processes are often opaque. Ethical concerns also arise regarding authorship, accountability, and data privacy. To integrate LLMs responsibly, transparency about their use and human oversight are essential. When applied thoughtfully, these tools can enhance scientific discovery, education, and healthcare delivery while maintaining the rigor and ethical standards that underpin medical science.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Amir Tahavvori
creator: Reza Judi Chelan
creator: Sima Aminoleslami
creator: Omid Fakharzadeh Moghadam
creator: Leili Haghighi
creator: Yeganeh Abdian
creator: Mohammad Hossein Naderi
creator: Amin Kanani
creator: Nikta Taghipour
creator: Amirali Farshid
creator: Seyedeh Tabasom Nejati
creator: Pouya Kalantari
creator: Pouran Varvani Farahani
creator: Sahar Jafarpour
creator: Amirreza Bahari
creator: Seyyed Erfan Hosseini Asl
creator: Seyyedeh Baran Hosseini Asl
creator: Zeinab Mohammadi
creator: Houman Bahrami Rad
creator: Sajad Teimoury
creator: Tara Abdolahyfard
creator: Edris Habibi
creator: Mohammad Eslami
creator: Saman Abdollahpour
creator: Sanaz Amiri Marbini
creator: Niloofar Taheri
creator: Dariush Moradi
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-10-09
publication date: 2025-10-09
starting page: 1
ending page: 222

Application of AI in Research and Data Science
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description: Artificial intelligence (AI) has become an essential component of modern research and data science, transforming how knowledge is generated, analyzed, and applied. Its integration into research workflows has accelerated discovery across disciplines by enabling the processing of vast and complex datasets that would be impossible for humans to analyze manually. Through techniques such as machine learning, deep learning, and natural language processing, AI identifies patterns, correlations, and causal relationships within data, facilitating new insights and predictive modeling. In data science, AI algorithms automate data cleaning, integration, and analysis, enhancing accuracy and efficiency. Predictive analytics models help forecast trends and outcomes in areas such as healthcare, economics, and environmental science. In biomedical research, AI assists in identifying genetic markers, analyzing medical images, and accelerating drug discovery. In the social sciences, it processes large volumes of text and social media data to detect behavioral patterns and public sentiment. AI also supports research reproducibility and transparency by automating statistical validation and optimizing experimental design. Natural language processing tools are increasingly used to scan scientific literature, summarize findings, and identify emerging research trends, thereby reducing the time required for literature reviews. Moreover, AI-driven simulations and optimization models allow researchers to test hypotheses virtually before conducting physical experiments, saving resources and time. Ultimately, the application of AI in research and data science is reshaping scientific inquiry into a more data-driven, efficient, and interdisciplinary process, enhancing the capacity of researchers to address complex global challenges with unprecedented speed and precision.
subject: Scholarly Peer-reviewed Books
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creator: Reza Rahaeimehr
creator: Zahra Babakhani
creator: Omid Fakharzadeh Moghadam
creator: Seyedmohammadmahan Mir Nasir
creator: Parisa Safaei
creator: Mir Ali Asghar Abdollahi
creator: Mina Bakhtiari Haftlang
creator: Ghazaleh Baghaei-Shiva
creator: Nasrin Salimian
creator: Nima Taheri Hosseinkhani
creator: Sanaz Abedi
creator: Niloufar Alinasab
creator: Maryam Damiri
creator: Fatemeh Amiri
creator: Reza Arabshahi
creator: Sina Montazeri
creator: Sogand Fattahiamin
creator: Ali Mahbod
creator: Nastaran Bahadori
creator: Negin Rabiei
creator: Saeed Hasani Mehraban
creator: Seyedehroshanak Haghighibardineh
creator: Kimia Kowsari
creator: Ali Amiri
creator: Mohsen Nakhaie
creator: Fatemeh Khodadadpour Mahani
creator: Elham Yazdantalab
creator: Ali Zafar Jafarzadeh
creator: Sadaf Taheri
creator: Neda Gorjizadeh
creator: Habib Mohammadpoor
creator: Mohammad Eslami
creator: Saman Abdollahpour
creator: Sanaz Amiri Marbini
creator: Dariush Moradi
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-10-07
publication date: 2025-10-07
starting page: 1
ending page: 362

Explainable Artificial Intelligence for Reducing the Global Cancer Burden
type: item
description: Explainable Artificial Intelligence (XAI) has emerged as a powerful approach for reducing the global cancer burden by enhancing transparency, trust, and clinical impact in oncology. Traditional AI models often operate as “black boxes” that provide results without clear reasoning, which limits their acceptance in clinical practice. XAI addresses this issue by offering interpretable insights into how predictions are generated, allowing clinicians to verify results against established medical knowledge and patient-specific conditions. In cancer diagnosis, XAI can show which imaging characteristics, genomic alterations, or clinical variables most strongly influence an outcome, supporting earlier and more reliable detection. This interpretability reduces the risk of misdiagnosis and increases physician confidence in AI-assisted tools. In treatment planning, XAI helps identify relevant patterns within complex datasets such as tumor genomics and patient records. This transparency clarifies why certain therapies may be more effective for particular individuals and advances the goals of precision medicine. Beyond individual care, XAI can benefit cancer control efforts at a global level. When screening and risk prediction systems are transparent, they are more likely to be trusted, adopted, and regulated in diverse healthcare settings, including those with limited resources. Clear explanations support policymakers, regulatory agencies, and clinicians in ensuring that AI tools are applied ethically and equitably. By combining predictive accuracy with interpretability, XAI provides not only technological advancement but also a pathway to improve equity in cancer care. Its integration can accelerate early detection, optimize therapies, and ultimately reduce the worldwide cancer burden.
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creator: Fatemeh Hedayati
creator: Reza Judi Chelan
creator: Mahfam Alijaniha
creator: Kamyab Komaee Koma
creator: Parsa Irajian
creator: Negar Rajabi
creator: Maryam Khosravi
creator: Kourosh Shahraki
creator: Behnoosh Omidvar
creator: Ahmad Jalali
creator: Sepideh Sadat Babaei
creator: Negin Rabiei
creator: Farbod Tabasi Kakhki
creator: Fatemeh Abediankenari
creator: Omid Fakharzadeh Moghadam
creator: Behnam Hoorshad
creator: Sina Asadollahi
creator: Sara Razi
creator: Amir Arshia Beheshti
creator: Sina Montazeri
creator: Sadaf Taheri
creator: Nastaran Nemati
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-09-09
publication date: 2025-09-09
starting page: 1
ending page: 195

Artificial Intelligence in Biomarker Discovery: Applications Across Medical Specialties
type: item
description: Artificial intelligence has emerged as a transformative force in biomarker discovery, reshaping how clinicians and researchers identify, validate, and apply indicators of disease across a wide spectrum of medical specialties. Traditional biomarker research is often hindered by the sheer complexity and heterogeneity of biological data, making it difficult to detect subtle patterns that link molecular, cellular, imaging, and clinical features to disease outcomes. AI overcomes these barriers by applying advanced machine learning and deep learning algorithms capable of analyzing large, multi-modal datasets and uncovering relationships that may remain hidden using conventional approaches. In oncology, AI-driven biomarker discovery integrates genomic, transcriptomic, and radiomic data to identify predictive signatures that guide precision therapies and improve early detection of cancers. In cardiology, AI analyzes imaging and proteomic biomarkers to predict cardiovascular risk and monitor treatment responses, enabling more personalized interventions. Neurology benefits from AI models that process neuroimaging, genetic data, and digital phenotyping to uncover biomarkers for complex disorders such as Alzheimer’s disease and multiple sclerosis. Similarly, in autoimmune and infectious diseases, AI enables integration of immune profiling with clinical and molecular data, advancing the identification of biomarkers for early diagnosis, prognosis, and therapeutic monitoring. Beyond specialty-specific applications, AI supports a broader shift toward personalized medicine by identifying biomarker combinations that reflect individual patient profiles. While challenges such as data quality, interpretability, and regulatory validation remain, the integration of AI in biomarker discovery promises to accelerate innovation and improve healthcare outcomes across disciplines.
subject: Scholarly Peer-reviewed Books
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creator: Mobina Gheibi
creator: Yasamin Rajabloo
creator: Yalda Alipour-Khabir
creator: Pouria Azami
creator: Sepideh Louia
creator: Tahmineh Ezazi Bojnordi
creator: Mahdi Javadian
creator: Masoud JahanbakhshJavid
creator: Masih Kavian
creator: Negar Rajabi
creator: Farbod Bigdeli
creator: Amir Ali Belbasi
creator: Shabnam Zolghadr Asli
creator: Sargol Assadi
creator: Fatemeh Ebrahimi
creator: Mostafa Ahangarian
creator: Negin Rabiei
creator: Fatemeh Mosayyebi
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-16
publication date: 2025-08-16
starting page: 1
ending page: 209

Intelligent Patient Engagement: Education and Follow-Up through AI and Telemedicine
type: item
description: Artificial intelligence and telemedicine are reshaping patient engagement by enabling more personalized, continuous, and efficient healthcare experiences. Intelligent systems can adapt educational content to match individual patient needs, comprehension levels, and medical conditions. This approach ensures that patients better understand their diagnoses and treatment plans, which can improve adherence and overall outcomes. AI-powered virtual assistants can answer patient questions in real time, provide medication reminders, and guide users through complex care instructions with clarity and precision. Telemedicine platforms enhanced by AI also play a vital role in follow-up care. These systems can monitor symptoms, vital signs, and behavioral data remotely, allowing healthcare providers to track patient progress between visits. Predictive analytics help identify potential health risks early, enabling timely clinical interventions that can prevent complications. Automated follow-up systems reduce the administrative burden on clinicians and ensure that no patient is overlooked, especially in busy or resource-limited settings. For individuals living with chronic diseases or in rural areas, AI-integrated telehealth ensures regular communication with healthcare teams, promoting trust and continuous support. Adaptive interfaces with multilingual capabilities help overcome communication barriers and make healthcare more inclusive and patient-centered. Together, AI and telemedicine support a proactive approach to care. They enhance the quality and reach of patient education and follow-up, contributing to better outcomes, greater engagement, and a more equitable healthcare system that responds effectively to individual and population needs.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Khadijeh Harati
creator: Horrieh Abbasmofrad
creator: Mahsa Ebrahimi
creator: Leila Hashemlu
creator: Reza Judi Chelan
creator: Ali Hashemzadeh
creator: Bita Zargaran
creator: Aysouda Jafari-Nakhjavanlou
creator: Fatemeh Amini
creator: Shabnam Asghari Amrei
creator: Saman Mahavarpour
creator: Negisa Seyyedi
creator: Shabahang Moghaddasi Esfivashi
creator: Mohammad Eslami
creator: Farzaneh Kianifar
creator: Shahriyar Azizi Nezhad Mashaki
creator: Negin Rabiei
rights: Copyright (c) 2025 Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-04
publication date: 2025-08-04
starting page: 1
ending page: 185

AI in Medical Imaging and Early Disease Detection
type: item
description: Artificial Intelligence (AI) has emerged as a transformative force in the field of medical imaging, playing a critical role in the early detection of various diseases. By leveraging machine learning and deep learning algorithms, AI systems can analyze complex imaging data with remarkable speed and accuracy, often surpassing traditional diagnostic methods in sensitivity and consistency. In early disease detection, timely and accurate diagnosis is essential for effective treatment and improved patient outcomes. AI-enhanced imaging tools can identify subtle patterns and abnormalities in modalities such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound—patterns that may be missed by even experienced clinicians. This capability is particularly valuable for detecting early signs of cancer, cardiovascular conditions, neurological disorders, and infectious diseases. AI also facilitates automated segmentation, classification, and quantification of lesions or anatomical structures, reducing diagnostic errors and interobserver variability. Furthermore, it enables the integration of multimodal data, including radiological images, clinical records, and genomic information, to support more comprehensive diagnostic insights and personalized treatment strategies. Beyond diagnosis, AI plays a role in predicting disease progression and monitoring treatment response, contributing to precision medicine. As research advances and more high-quality datasets become available, the performance and generalizability of AI models continue to improve. Despite existing challenges such as data privacy, regulatory approval, and integration into clinical workflows, the potential of AI to revolutionize early disease detection through medical imaging is profound, offering hope for more proactive, efficient, and equitable healthcare delivery.
subject: Scholarly Peer-reviewed Books
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creator: Vida Niakosari
creator: Reza Mosaddeghi-Heris
creator: Hossein Boustani Hezarani
creator: Mehrdad Farrokhi
creator: Parisa Safaei
creator: Hessam Nikseresht
creator: Nasrin Etesamifard
creator: Parham Heidari
creator: Kiana Bahmanipour
creator: Seyedhesamoddin Khatami
creator: Maryam Dourandeesh
creator: Pouyan Rahimi Bodagh
creator: Sina Janbozorgi
creator: Seyedeh Tabasom Nejati
creator: Mohammad Bdaqli
creator: Ali Aghajan
creator: Fatemeh Amini
creator: Saba Mehrtabar
creator: Mohammad HasanzadehBidgoli
creator: Sadegh Bagherzadeh
creator: Bita Zargaran
creator: Fereshteh Karbasian
creator: Mahya Naghipoor-Alamdari
creator: Amirreza Khalaji
creator: Saman Mahavarpour
creator: Amirali Fallahian
creator: Amir H Fallahian
creator: Rana Hashemi
creator: Amirhossein Tayebi
creator: Mojan Ayati
creator: Samaneh Ghasemipour
creator: Nazanin Hedayati Amlashi
creator: Mohammad Sobhanardekani
creator: Hadi Khanifar
creator: Lida Zare Lahijan
creator: Paniz Sabeghi
creator: Seyed Mojtaba Ghorani
creator: Arezou Soltanattar
creator: Saeid Bolhasani
creator: Alisina Mousavi
creator: Atena Talebpoor Amirhandeh
creator: Farzaneh Kianifar
creator: Mohammad Eslami
creator: Saman Abdollahpour
creator: Kamyar Khorsand
creator: Hamed Sabzehie
creator: Negin Rabiei
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-07-16
publication date: 2025-07-16
starting page: 1
ending page: 203

Artificial Intelligence in Cancer Genomics: Transforming Diagnosis, Treatment, and Precision Medicine
type: item
description: Artificial intelligence is revolutionizing the field of cancer genomics by enabling the rapid interpretation of complex and high-dimensional molecular data. Traditional genomic analyses often face limitations when processing the vast amount of sequencing information generated from tumor samples. AI algorithms, including machine learning and deep learning models, excel in identifying hidden patterns and associations within this data, leading to earlier and more accurate cancer diagnosis. By integrating genomic, transcriptomic, and epigenetic information, AI facilitates the classification of tumor subtypes, prediction of disease progression, and identification of actionable genetic alterations. In the context of treatment, AI supports the selection of personalized therapies by analyzing tumor-specific molecular features and matching them with appropriate drugs. This capability is central to the advancement of precision oncology, where individualized treatment strategies are tailored to each patient’s unique genetic profile. AI also contributes to ongoing treatment evaluation by monitoring response and detecting emerging resistance through longitudinal data, including liquid biopsy and circulating tumor DNA analyses. Furthermore, AI enhances clinical decision-making by powering predictive models and intelligent support systems that help oncologists design personalized treatment plans. These innovations improve patient outcomes, optimize therapeutic effectiveness, and reduce the burden of unnecessary interventions. As AI continues to integrate with cancer genomics, it is ushering in a transformative era in oncology, enabling more precise diagnosis, targeted therapies, and patient-centered care based on comprehensive molecular insights.
subject: Scholarly Peer-reviewed Books
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creator: Sepideh Louia
creator: Reza Mosaddeghi-Heris
creator: Radin Kamvar
creator: Neda Zahmatkesh
creator: Maryam Damiri
creator: Mahdis Abdar Esfahani
creator: Mobina Gheibi
creator: Seyedeh Sara Alemohammad
creator: Vahid Jafari
creator: Mehrsa Tavangar
creator: Ali Mazdak
creator: AliMohammad Keshavarz
creator: Raha Rouhbakhsh Azimi
creator: Hamed Ghorbani
creator: Ali Aghajan
creator: Seyedeh Tabasom Nejati
creator: Seyedeh Farinaz Fattahpour
creator: Pardis Zamani
creator: Erfan Barootchi
creator: Seyede Helma Naseri Sadr
creator: Arezou Soltanattar
creator: Forough Jannesari
creator: Reyhane Nematollahi
creator: Amirali Fallahian
creator: Amir H Fallahian
creator: Fatemeh Boroumandfar
creator: Zahra Khalili Torbehbar
creator: Roozbeh Roohinezhad
creator: Seyed Kiavash Sajadi
creator: Parnia Zarei
creator: Ehsan Goudarzi
creator: Amirhossein Tayebi
creator: Kian Farahani
creator: Aida Amanat
creator: Sedighe Yosefi
creator: Farhan Musaie
creator: Armita Jokar-Derisi
creator: Mohammad Mehdi Atarod
creator: Fatemeh Sahebekhtiari
creator: Sepide Javankiani
creator: Amir Nasrollahizadeh
creator: Bahareh Shoshtari-Yeganeh
creator: Mohammadreza Moeininejad
creator: Shakila Amirghasemi
creator: Seyyed Erfan Hosseiniasl
creator: Seyyedeh Baran Hosseiniasl
creator: Shima Moradian-Lotfi
creator: Seyedeh Maryam Paranchi
creator: Mohsen Farshi
creator: Reza Habibi
creator: Sara Yazdizadeh
creator: Parham Rahmani
creator: Fatemeh Rostamian Motlagh
creator: Fardis Sattari
creator: Negin Rabiei
creator: Elmira Fardi
rights: Copyright (c) 2025 Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2025-06-26
publication date: 2025-06-26
starting page: 1
ending page: 234

The Future of Prosthetics and Organ Transplantation: A Therapeutic Approach Across Various Medical Disciplines
type: item
description: The future of prosthetics and organ transplantation is rapidly advancing beyond traditional boundaries, offering transformative potential across multiple medical disciplines. Innovations in biomedical engineering, regenerative medicine, and immunology are reshaping how we approach the replacement and restoration of tissues and organs. From cochlear implants in otolaryngology and bionic limbs in orthopedics to artificial pancreases in endocrinology and face or uterus transplants in reconstructive surgery, the integration of technology and biology is enabling personalized, functional, and life-enhancing therapies. Emerging fields such as 3D bioprinting and stem cell-based organ engineering are pushing toward the development of lab-grown organs that may one day eliminate the need for donor tissues. Neuroprosthetics, powered by brain-computer interfaces, are opening new avenues in neurology and rehabilitation, restoring movement and communication in patients with paralysis or neurodegenerative disorders. Artificial intelligence and robotics are enhancing surgical precision, while smart prosthetics provide real-time adaptability and sensory feedback. As these technologies become more sophisticated and accessible, their application is expanding into complex, multidisciplinary care models. The convergence of science, surgery, and ethics will be critical to ensure equitable access, long-term safety, and meaningful integration into healthcare systems. Ultimately, prosthetics and transplantation are not only extending lives but redefining the possibilities of recovery and human potential across the full spectrum of medicine.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Khadijeh Harati
creator: Maryam Tahernejad
creator: Shahad Mohammed Saddam Saddam
creator: Mohsen Farshi
creator: Mahbubeh Saeedfar
creator: Mobina Gheibi
creator: Mohammad Khajehei
creator: Kamyab Komaee Koma
creator: Khotan Sardari
creator: Seyyede Fatemeh Asghari
creator: Amirsalar Motamedi
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-05-25
publication date: 2025-05-25
starting page: 1
ending page: 193

Artificial Intelligence in Genomic Medicine: Improving Diagnostic Accuracy and Treatment Outcomes
type: item
description: Artificial intelligence (AI) is revolutionizing genomic medicine by enhancing the speed, accuracy, and efficiency of genetic data analysis. With the explosion of genomic information generated through technologies like next-generation sequencing, traditional analytical methods often fall short in identifying complex patterns within vast datasets. AI algorithms, particularly machine learning and deep learning models, can process and interpret these massive datasets with remarkable precision. This capability allows for the discovery of novel genetic markers, risk factors, and disease mechanisms that were previously undetectable through conventional methods. One of the most significant contributions of AI in genomic medicine is the improvement in diagnostic accuracy. AI-driven tools can integrate genomic data with clinical, imaging, and biochemical information to predict disease risk, identify early-stage pathologies, and provide more accurate diagnoses. In oncology, for example, AI models can detect mutations linked to various cancers, guiding personalized treatment plans that target specific genetic alterations. Moreover, AI enhances treatment outcomes by facilitating precision medicine approaches. By analyzing individual genetic profiles, AI helps clinicians select the most effective therapies, predict patient responses to specific drugs, and monitor disease progression in real time. This personalized approach minimizes trial-and-error treatments and reduces adverse drug reactions, leading to better patient outcomes. As AI continues to evolve, its integration with genomic medicine holds the potential to transform healthcare, making it more predictive, preventive, personalized, and participatory. Future innovations will likely further bridge the gap between complex genetic insights and practical clinical applications.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Mitra Ramezanian
creator: Dorsa Sadeghy Benis
creator: Reza Nikakhtar
creator: Neda Gorjizadeh
creator: Fatemeh Asadi
creator: Mobina Bagherianlemraski
creator: Nastaran Kazemi Rad
creator: Pedram Sarikhani
creator: Ali Rezvanimehr
creator: Seyyede Fatemeh Asghari
creator: Sadegh Bagherzadeh
creator: Mozhdeh Karmi
creator: Kosar Kohandel
creator: Aida Saki
creator: Rana Hashemi
creator: Sara Moghimi
creator: Ehsan Goudarzi
creator: Fahimeh Akbarian
creator: Firoozeh Faridanjahromi
creator: Anahita Heydari
creator: Hoda Maleki
creator: Ali Aghajan
creator: Maryam Rostampour
creator: Mohammad Sharif Sharifani
creator: Mona Pishgahpour
creator: Sara Montazeri Namin
creator: Alireza Mohammad Bigloo
creator: Fateme Sadooghi
creator: Nikta Taghipour
creator: Niloufar Jabbari
creator: Mahzad Rahmani
creator: Alireza Abbaszadeh
creator: Zhenus Ezzatpanah
creator: Roozbeh Roohinezhad
creator: Saba Dangpiaei
creator: Sadaf Salehi
creator: Mohammadamin Sabbagh Alvani
creator: Maryam Azimi
creator: Parham Rahmani
creator: Fatemeh Rostamian Motlagh
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-05-06
publication date: 2025-05-06
starting page: 1
ending page: 215

The Brain-Body Connection: Neuroscience’s Role Across Medical Sciences Disciplines
type: item
description: The brain-body connection is a foundational principle in modern medical science, highlighting the intricate and dynamic communication between the central nervous system and various physiological systems. Neuroscience plays a pivotal role in unraveling this connection, offering insights into how neural circuits influence, and are influenced by, bodily functions across a wide range of medical disciplines. In cardiology, for instance, neurocardiology explores how the brain regulates heart rhythms and blood pressure through autonomic pathways. Similarly, in endocrinology, neuroendocrine mechanisms govern hormonal secretion, integrating stress responses and metabolic regulation. In gastroenterology, the gut-brain axis exemplifies the bidirectional flow of information between the nervous system and gastrointestinal tract, affecting digestion, mood, and immune responses. Rheumatology benefits from neuroscience through understanding neuroimmune interactions that contribute to inflammation and chronic pain in autoimmune diseases. In dermatology, the emerging field of psychodermatology reveals how emotional stress can manifest in skin conditions such as psoriasis and eczema. Furthermore, nephrology and hematology are increasingly recognizing the role of neurological regulation in kidney function and blood homeostasis, respectively. These interdisciplinary insights underscore the central role of the brain in maintaining physiological balance and guiding therapeutic approaches. As neuroscience continues to expand, its integrative contributions across disciplines are essential for advancing precision medicine and holistic patient care.
subject: Scholarly Peer-reviewed Books
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creator: Aida Javadzadeh
creator: Daniel Shafiei
creator: Roghaye Safarpour Amlash
creator: Reyhaneh Mehrvar
creator: Susan Sepehrian
creator: Atefe Shafiee
creator: Sahar Nasrollahi
creator: Arefeh Solgi
creator: Samira Amin Afshari
creator: Farya Azimi
creator: Sara Moghimi
creator: Zahra Barati Farimani
creator: Managol Kayyal
creator: Maryam Hadi Sichani
creator: Pegah Hosseini
creator: Seyed Mohammad Shahab Mirabedini
creator: Saeid Bolhasani
creator: Sara Montazeri Namin
creator: Seyed Ali Shariat Razavi
creator: Dorsa Zareie
creator: Zahra Hashempour
creator: Rana Hashemi
creator: Mahya Asadalizadeh
creator: Nafiseh Khalilian
creator: Ghazaleh Baghaei-Shiva
creator: Mohsen Farshi
creator: Mahdi Aghaalikhani
creator: Soophia Mehrjooy
creator: Niloufar Jabbari
creator: Parham Rahmani
creator: Reza Mosaddeghi-Heris
creator: Mina Rahmani Sani
creator: Meshkat Omrannezhad
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-04-19
publication date: 2025-04-19
starting page: 1
ending page: 210

The AI Revolution: Predicting and Managing the Next Global Health Challenges and Emerging Disease Outbreaks
type: item
description: The AI revolution is reshaping global health by enabling the prediction and management of emerging disease outbreaks with unprecedented precision. Artificial intelligence leverages vast datasets from diverse sources—such as satellite imagery, social media, and genomic sequencing—to identify patterns that signal potential health threats. Machine learning algorithms can analyze environmental changes, animal migration patterns, and human mobility to forecast outbreaks before they occur. For instance, AI systems have successfully predicted the spread of diseases like Zika and Ebola by correlating climate data, population density, and travel routes. In managing outbreaks, AI enhances real-time monitoring and response strategies. Natural language processing tools scan news articles and public health reports to detect early warning signs, while predictive models optimize resource allocation for vaccines and medical supplies. AI-powered diagnostic tools also accelerate disease identification, reducing the time between symptom onset and treatment. During the COVID-19 pandemic, AI models analyzed viral genomes to track mutations and inform vaccine development. Despite its promise, the AI revolution faces challenges, including data privacy concerns, algorithmic biases, and unequal access to technology. Ensuring ethical implementation and equitable distribution of AI tools is critical to addressing these issues. By fostering international collaboration and investing in scalable solutions, AI can transform global health security, equipping humanity to anticipate and combat future pandemics more effectively. The integration of AI into public health systems represents a paradigm shift, empowering proactive rather than reactive responses to emerging health challenges.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Khadijeh Harati
creator: Reza Mosaddeghi-Heris
creator: Kiarash Kiani
creator: Mona Saligheh Rad
creator: Reza Morovatshoar
creator: Mohammad Kamali
creator: Mohadeseh Ghasemi
creator: Sanam Faizabadi
creator: Aryan Madady
creator: Negin Sina
creator: Somaye Arabi
creator: Mehrafarin Naraki
creator: Sadegh Bagherzadeh
creator: Mansoureh Fatahi
creator: Fatemeh Naseri Atashani
creator: Roozbeh Roohinezhad
creator: Kourosh Amirian Shayesteh
creator: Sudabeh Fotoohi Piraghaj
creator: Aref Andishgar
creator: Hooman Esfahani
creator: Saeid Ali Zadeh
creator: Bahareh Salekani
creator: Ali Aghajan
creator: Parham Rahmani
rights: Copyright (c) 2025 Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2025-03-23
publication date: 2025-03-23
starting page: 1
ending page: 326

Robotics in Healthcare
type: item
description: Robotics has revolutionized healthcare by enhancing precision, efficiency, and accessibility across various medical fields. From robotic-assisted surgeries to rehabilitation and patient care, these technologies have significantly improved outcomes for both patients and healthcare providers. Robotic surgical systems, such as the da Vinci Surgical System, allow for minimally invasive procedures with greater accuracy, reduced complications, and faster recovery times. These systems provide enhanced dexterity and precision, enabling surgeons to perform complex procedures with minimal incisions. Beyond surgery, robotics plays a crucial role in rehabilitation, where robotic exoskeletons and assistive devices help patients regain mobility after injuries or neurological disorders like stroke or spinal cord damage. In diagnostics, robotic technologies, such as automated laboratory systems and AI-powered imaging tools, facilitate faster and more accurate disease detection, improving early diagnosis and treatment planning. Additionally, robotics is transforming patient care with robotic nurses and assistants, which help monitor patients, administer medications, and perform routine tasks, reducing the burden on healthcare staff. Telepresence robots enable remote consultations, allowing specialists to assess and manage patients from different locations. The integration of artificial intelligence with robotics further enhances capabilities, enabling personalized treatments and predictive analytics for disease management. As technology advances, robotics in healthcare will continue to expand, making medical procedures safer, improving patient outcomes, and increasing accessibility to quality healthcare worldwide. The ongoing development of robotic solutions promises a future where healthcare is more precise, efficient, and patient-centered.
subject: Scholarly Peer-reviewed Books
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creator: Pegah Babaheidarian
creator: Arezou Soltanattar
creator: Seyed Kiavash Sajadi
creator: Leila Rostamian
creator: Laleh Foroutani
creator: Tina Soleymanpourshamsi
creator: Elham Zarrazvand
creator: Amirali Farshid
creator: Mehdi Dadpour
creator: Sina Janbozorgi
creator: Fatemeh Amini
creator: Amineh Andjomshoaa
creator: Yasaman Asadi
creator: Mahdi Faraji
creator: Parham Rahmani
creator: Sepideh Hassanpour Khodaei
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-02-20
publication date: 2025-02-20
starting page: 1
ending page: 178

Innovative Vaccination: A New Era in Cancer Prevention
type: item
description: Cancer remains one of the leading causes of death worldwide, prompting researchers to explore novel prevention and treatment strategies. One of the most promising advancements in oncology is the development of innovative cancer vaccines. Unlike traditional vaccines that primarily prevent infectious diseases, cancer vaccines are designed to stimulate the immune system to recognize and eliminate cancerous cells. These vaccines hold great potential in both cancer prevention and treatment, ushering in a new era of precision medicine. Preventive cancer vaccines aim to protect against viruses known to cause malignancies. The most notable examples include the human papillomavirus (HPV) vaccine, which prevents cervical and other HPV-related cancers, and the hepatitis B vaccine, which reduces the risk of liver cancer by preventing hepatitis B virus infection. These vaccines have significantly reduced cancer incidence in vaccinated populations, highlighting the effectiveness of immunization as a preventive measure. On the other hand, therapeutic cancer vaccines work by boosting the immune system’s ability to detect and destroy tumor cells. Advances in vaccine technology, such as peptide-based, dendritic cell, and mRNA vaccines, are being explored for various cancers, including melanoma, lung, and breast cancer. With ongoing research and clinical trials, cancer vaccination is poised to revolutionize cancer prevention and treatment. As immunotherapy continues to evolve, innovative vaccination strategies offer hope for reducing cancer burden and improving patient outcomes worldwide.
subject: Scholarly Peer-reviewed Books
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creator: Mehrdad Farrokhi
creator: Nogol Ghalamkarpour
creator: Shadi Nouri
creator: Mahdi Babaei
creator: Yasamin Rajabloo
creator: Mahtab Sattari
creator: Atousa Ghorbani
creator: Vahid Jafari
creator: Seyed Amir Hossein Mohammadzadeh Hosseini Moghri
creator: Ayda Khalaj
creator: Zahra Hashempour
creator: Parnian Gourani
creator: Zahra Mogharari
creator: Parsa Chaeibakhsh Langeroudi
creator: Ali Mansoursamaei
creator: Alireza Khanahmad
creator: Alireza Mohammad Bigloo
creator: Amirhossein Rigi
creator: Sara Moghimi
creator: Mohammad Amin Hashemnejad
creator: Elham Oveili
creator: Noushin Afshar Moghaddam
creator: Mohammad Eslami
creator: Saman Abdollahpour
creator: Farzaneh Kianifar
creator: Khadijeh Bagtash
creator: Mohammad Hassan Zoofaghari
creator: Fatemeh Kalaki Jouybari
creator: Pegah Babaheidarian
creator: Paria Babaahmadi
rights: Copyright (c) 2025 Kindle and PreferPub https://creativecommons.org/licenses/by-nc/4.0
date: 2025-02-01
publication date: 2025-02-01
starting page: 1
ending page: 194

AI-Driven Strategies for Improving Patient Quality of Life
type: item
description: Artificial intelligence (AI) has emerged as a transformative tool in healthcare, offering innovative solutions to enhance patient quality of life (QoL). By leveraging machine learning algorithms, natural language processing, and predictive analytics, AI enables personalized care, early disease detection, and improved treatment outcomes. One key area where AI has made significant strides is in chronic disease management. Conditions such as diabetes, cardiovascular diseases, and chronic pain can be monitored continuously through wearable devices and mobile health apps. These technologies track vital signs, alert patients and physicians to potential complications, and provide tailored recommendations for lifestyle modifications, thereby empowering patients to take an active role in their care. In the realm of mental health, AI-driven chatbots and virtual therapists offer accessible, stigma-free support to individuals experiencing anxiety, depression, or stress. These tools provide real-time guidance, track emotional patterns, and integrate seamlessly with traditional therapy, improving mental health outcomes. AI is also revolutionizing cancer care through precision oncology. Algorithms analyze vast datasets, including genomic profiles and medical records, to identify optimal treatment strategies for individual patients. This personalized approach enhances therapeutic efficacy and minimizes side effects, significantly improving the QoL for cancer patients. Moreover, AI enhances diagnostic accuracy by analyzing medical images and clinical data with unparalleled speed and precision. For example, AI tools in radiology and pathology reduce diagnostic errors, enabling earlier interventions and better prognoses. Despite its immense potential, challenges such as ethical concerns, data security, and algorithm biases must be addressed to maximize the benefits of AI. By fostering collaboration between technologists, clinicians, and policymakers, AI-driven strategies can be refine…
subject: Scholarly Peer-reviewed Books
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creator: Erfan Rahmani
creator: Masoud Farrokhi
creator: Ali Aghajan
creator: Golsa Gholampour
creator: Erfan Ghoodjani
creator: Ramtin Shemshadigolafzani
creator: Fatemeh Gheibi
creator: Arya Tarassodi
creator: Leila Rostamian
creator: Parinaz Taheri
creator: Mohsen Firoozi
creator: Dalia Sharifi
creator: Nastaran Nemati
creator: Pegah Babaheidarian
creator: Horrieh Abbasmofrad
creator: Saeid Ali Zadeh
creator: Bahareh Salekani
creator: Golnaz Dadpour
creator: Parham Rahmani
rights: Copyright (c) 2025 Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2025-01-22
publication date: 2025-01-22
starting page: 1
ending page: 214

Global Health Challenges
type: item
description: Global health faces numerous challenges that significantly impact populations worldwide. These challenges stem from a combination of epidemiological, social, economic, and environmental factors, requiring coordinated international efforts to address them effectively. Non-communicable diseases (NCDs), such as cardiovascular diseases, diabetes, cancer, and chronic respiratory diseases, are among the leading causes of death globally. Their rise is fueled by aging populations, urbanization, unhealthy diets, sedentary lifestyles, and tobacco and alcohol use. These diseases strain healthcare systems, particularly in low- and middle-income countries (LMICs), where resources are often insufficient to manage their growing burden. Addressing these requires preventive measures, early detection, and equitable access to treatment. Infectious diseases remain a persistent challenge, particularly in LMICs. Diseases such as malaria, tuberculosis, and HIV/AIDS continue to affect millions. Additionally, global threats like antimicrobial resistance and emerging infections, such as COVID-19, highlight vulnerabilities in public health systems and the need for global preparedness, robust surveillance, and rapid response mechanisms. Healthcare disparities exacerbate these challenges. Many regions lack adequate healthcare infrastructure, trained professionals, and affordable treatments. Inequities in access to care are stark, particularly in rural areas and among marginalized populations, perpetuating poor health outcomes. Environmental factors, including climate change, air pollution, and inadequate water and sanitation, also contribute to the global health burden. Rising temperatures and extreme weather events increase the spread of vector-borne diseases, exacerbate food insecurity, and displace vulnerable populations. Addressing global health challenges requires collaborative international policies, sustainable financing, and investments in public health infrastructure and education. A m…
subject: Scholarly Peer-reviewed Books
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creator: Erfan Rahmani
creator: Mehrdad Farrokhi
creator: Parisa Nemati
creator: Sanaz Riahi
creator: Mahshid Esmaielzade Rostami
creator: Ramtin Shemshadi Golafzani
creator: Fatemeh Gheibi
creator: Fatemeh Faraji
creator: Amirhossein Rigi
creator: Yasamin Rajabloo
creator: Hadi Khanifar
creator: Fatemeh Azarkish
creator: Fatemeh Keshvari-Shad
creator: Parisa Doroudgar
creator: Negin Rabiei
creator: Manouchehr Nasrollahzadeh Saravi
creator: Ali Aghajan
creator: Fatemeh Asadi Talebbeigi
creator: Ramin Alizadeh Gheshlagh
creator: Mahsa Geravandi
creator: Ali Hajihashemi
creator: Mohammad Mohajer
creator: Morteza Alipour
creator: Horrieh Abbasmofrad
creator: Sadegh Bagherzadeh
creator: Maryam Hadi Sichani
creator: Zahra Yousefi Chekovari
creator: Hoora Morshedian
creator: Mohammad Mahdi Parish
creator: Pegah Gheshlaghi
creator: Roghaye Safarpour Amlash
creator: Azadeh Bagheri
creator: Hadi Assadian
creator: Zahra Jahani
creator: Rosemina Bahrololoom
creator: Golnoush Mohammadifar
creator: Sara Moghimi
creator: Seyedeh Farinaz Fattahpour
creator: Baharak Aghapour
creator: Amir Abderam
creator: Mehdi Dadpour
creator: Yasaman Hadi
creator: Soroush Abbasabadarabi
creator: Hasti Barzegar
creator: Sephora Khandan
creator: Parisa Yazdi
creator: Mehrsa Shiasi
creator: Koyar Hiwa Raouf
creator: Armita Firoozmand
creator: Zeynab Abdollahi
creator: Masoumeh Moallem
creator: Zahra Mehradfar
creator: Parham Rahmani
rights: Copyright (c) 2024 Kindle
date: 2023-12-28
publication date: 2023-12-28
starting page: 1
ending page: 218

AI and Deep Learning in Understanding the Etiology and Pathogenesis of Autoimmune Diseases
type: item
description: Autoimmune diseases arise when the immune system mistakenly attacks the body’s own tissues, leading to chronic inflammation and organ damage. These disorders are complex, influenced by genetic, epigenetic, environmental, and immunological factors. Despite extensive research, many aspects of their etiology and pathogenesis remain unclear. Artificial intelligence (AI) and deep learning (DL) have emerged as transformative tools in unraveling the complexities of autoimmune diseases. AI, with its ability to analyze large datasets, enables researchers to identify patterns and relationships that are otherwise difficult to detect. In the context of autoimmune diseases, AI is applied to analyze omics data—genomics, proteomics, transcriptomics, and metabolomics—to uncover genetic variants, immune pathways, and biomarkers associated with disease susceptibility and progression. For instance, machine learning (ML) algorithms have identified critical risk loci and differentially expressed genes in diseases such as rheumatoid arthritis and lupus. Deep learning, a subset of AI, excels in processing high-dimensional data and detecting intricate patterns. DL techniques have been employed in single-cell RNA sequencing to identify immune cell populations driving autoimmune responses. These models also integrate imaging and histopathological data to detect subtle tissue changes indicative of early disease onset. Moreover, AI-driven bioinformatics tools have advanced understanding of immune system dysregulation, including cytokine networks and immune cell interactions. They also help study environmental triggers, such as microbiome alterations, that influence autoimmunity. AI and DL are not only providing insights into disease mechanisms but also enhancing diagnostics, enabling personalized treatment strategies, and accelerating drug discovery. As these technologies continue to evolve, they promise to illuminate the complexities of autoimmune diseases, paving the way for innovative thera…
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creator: Amirhossein Rigi
creator: Khadijeh Harati
creator: Mohammadjavad Abbaspour
creator: Seyedeh Farinaz Fattahpour
creator: Pegah Hosseini
creator: Atousa Moghadam Fard
creator: Mina Hobbi
creator: Golsa Babapour
creator: Negar Babapour
creator: Naghmeh Nikben
creator: Parisa Doroudgar
creator: Reyhaneh Mehrvar
creator: Sara Hosseinmirzaei
creator: Nasim Razavi
creator: Hessam Nikseresht
creator: Vida Niakosari
creator: Reza Morovatshoar
creator: Peiman Mazaheri
creator: Seyed Mohammad Shahab Mirabedini
creator: Laya Taghipour
creator: Amirali Fallahian
creator: Hiva Rahmati
creator: Reza Babakhani
creator: Mohsen Heidari
creator: Morteza Alipour
creator: Shila Taherlou
creator: Azadeh Taherlou
creator: Mohammaderfan Ghazanfarpour
creator: Shaheen Shahriari
creator: Hossein Pilva
creator: Delnavaz Jan
creator: Sana Baghizadeh
creator: Hamed Sabzehie
creator: Niloofar Khansari Nejad
creator: Parham Rahmani
rights: Copyright (c) 2024 Kindle
date: 2024-12-06
publication date: 2024-12-06
starting page: 1
ending page: 182

Artificial Intelligence for Prediction of Metastasis Risk and Survival
type: item
description: Artificial Intelligence (AI) has emerged as a transformative tool in predicting metastasis risk and survival outcomes in cancer care. Traditional methods for assessing cancer progression and prognosis, such as imaging, biomarker analysis, and clinical staging systems, often have limitations in accounting for the intricate biological processes that influence metastasis. AI offers a significant advantage by leveraging machine learning algorithms and advanced data analysis techniques to process vast amounts of complex medical data, including genomic information, pathology images, and patient records. This approach enhances predictive accuracy and provides insights that can be crucial for personalized cancer treatment. Machine learning models, particularly deep learning algorithms, have shown promising results in analyzing imaging data for early detection of metastatic spread. By identifying patterns and features not easily discernible to the human eye, these AI-driven systems can predict metastasis risk with higher precision. Furthermore, AI models can integrate various data types, creating a holistic understanding of a patient’s cancer profile. This comprehensive analysis can improve survival predictions, guiding clinicians in selecting more effective, personalized therapeutic strategies. AI's potential extends beyond prediction, aiding in real-time decision-making and monitoring treatment responses. As research and technology advance, AI systems are expected to become an integral part of oncology, helping to optimize outcomes, reduce healthcare costs, and provide tailored interventions that could significantly improve patients’ quality of life and survival chances.
subject: Scholarly Peer-reviewed Books
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creator: Neda Zahmatkesh
creator: Sepideh Sadat Babaei
creator: Shokoufeh Habibi Manesh
creator: Mohammadjavad Abbaspour
creator: Erfan Ghadirzadeh
creator: Nasrin Salimian
creator: Aida Amanat
creator: Seyyed-Ghavam Shafagh
creator: SeyedAbbas Pakmehr
creator: Ehsan Bahrami Hezaveh
creator: Rana Hashemi
creator: Maryam Azarian
creator: Parvin Aghavali
creator: Amirali Farshid
creator: Amirmohammad Azizzadeh
creator: Sima Foroughi Nematollahi
creator: Amirali Fallahian
creator: Sara Moghimi
creator: Saeed Hasani Mehraban
creator: Sina Jabbari
creator: Safa Tahmasebi
creator: Amirhossein Esfahani
creator: Pouria Azami
creator: Kimia Kowsari
creator: Seyyed-Erfan Hosseini Asl
creator: Niloofar Khoshroo
creator: Seyyed Pouria Tafti
creator: Kiana Nouri
creator: Siavash Ketabi
creator: Sanam Hosseinpoor-Dashatani
creator: Kazem Abbaszadeh-Goudarzi
creator: Dorsa Zareie
creator: Fatemeh Farid
creator: Lida Zare Lahijan
creator: Hamed Sabzehie
creator: Amirhossein Rigi
creator: Fatemeh Mortazavi Moghadam
creator: Niloofar Khansari Nejad
creator: Parisa Safaei
rights: Copyright (c) 2024 Kindle
date: 2024-11-15
publication date: 2024-11-15
starting page: 1
ending page: 205

AI-Enhanced Virtual Clinics and Telemedicine for Cancer Treatment
type: item
description: AI-enhanced virtual clinics and telemedicine are transforming cancer treatment by improving access to care, diagnostic precision, and personalized treatment options. For patients, especially those in remote areas or with mobility challenges, telemedicine offers a lifeline, enabling them to consult with oncology specialists and receive essential follow-up care without needing to travel. When combined with AI, telemedicine becomes even more powerful. AI algorithms can analyze complex data, such as medical imaging, pathology results, and genomic information, to assist doctors in diagnosing cancers more accurately and tailoring treatment plans based on individual patient profiles. These virtual clinics use AI-powered tools to monitor patients’ progress, detect early signs of complications, and adjust treatment plans accordingly. For example, AI can track subtle changes in imaging that may indicate tumor growth or response to therapy, alerting physicians to potential issues before they become critical. Moreover, AI-driven predictive models can offer insights into prognosis and guide decision-making, making cancer treatment more proactive and personalized. As telemedicine continues to advance, AI-enhanced virtual clinics promise to make cancer care more accessible, efficient, and effective for patients worldwide.
subject: Scholarly Peer-reviewed Books
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creator: Hamidreza Amiri
creator: Melina Ghaneiyan
creator: Parisa Farjami
creator: Helena Mehran
creator: Sanam Mohammadzadeh
creator: Salar Ghaderi
creator: Yasaman Niakan
creator: Pendar Argani
creator: Maedeh Golnavaz
creator: Sara Moghimi
creator: Soroush Sadr
creator: Zahra Ovaisi
creator: Mahmonir Bayanati
creator: Fatemeh Amini
creator: Atefe Shafiee
creator: Zohreh Molaei
creator: Jouan Taheri Talesh
creator: Saeed Hasani Mehraban
creator: Golnar Mortaz Hejri
creator: Samaneh Ghasemipour
creator: Maryam Ahmadyan
creator: Mona Mohajeri Tehrani
creator: Ali Ebrahimi
creator: Saman Soltani Moghadam
creator: Mozhdeh Mohammadi Visroudi
creator: Yas Haririan
creator: Neda Seifi
creator: Pouria Azami
creator: Maryam Sharifi
creator: Nasim Nouri
creator: Shabnam Abbasian
creator: Shayan Ramazi
creator: Diar Zooravar
creator: Amirali Fallahian
creator: Parham Dastjerdi
creator: Javaneh Atighi
creator: Alireza Mohammad Bigloo
creator: Roghayeh Askari Noghanimoghadam
creator: Morteza Alipour
creator: Reza Zahedpasha
creator: Asma Razman
creator: Nadia Shafiee
creator: Azadeh Tadayonfard
creator: Shamim Chinian
creator: Hamed Sabzehie
creator: Noushin Afshar Moghaddam
creator: Mohammad Eslami
creator: Saman Abdollahpour
creator: Fatemeh Safaei
creator: Farzaneh Kianifar
creator: Khadijeh Bagtash
creator: Mohammadreza Fadavighafari
creator: Paradise Fatehi Shalamzari
creator: Amirhossein Rigi
rights: Copyright (c) 2024 Kindle https://creativecommons.org/licenses/by-nc/4.0
date: 2024-10-26
publication date: 2024-10-26
starting page: 1
ending page: 207

AI and Deep Learning in Understanding the Etiology and Pathogenesis of Cancers
type: item
description: Artificial intelligence (AI) and deep learning have emerged as powerful tools in understanding the etiology and pathogenesis of cancers. These technologies help uncover complex patterns in large datasets, offering insights into the genetic, environmental, and molecular factors that drive cancer development. By analyzing genomic and multi-omic data, AI can identify mutations, epigenetic changes, and signaling pathway disruptions that contribute to the onset and progression of various cancers. Deep learning models, particularly convolutional neural networks (CNNs), are adept at analyzing medical images, aiding in early cancer detection and diagnosis. They can detect subtle changes in tissue morphology, which helps differentiate between benign and malignant tumors. Moreover, AI can integrate genomic data with clinical information to predict disease progression and treatment outcomes, offering personalized therapeutic approaches. In the study of cancer pathogenesis, AI-driven models can simulate tumor growth and metastasis by mapping interactions within the tumor microenvironment, which includes immune cells, blood vessels, and extracellular matrix components. This allows researchers to explore how cancers evolve, invade, and resist therapies. Overall, AI and deep learning play a transformative role in cancer research, enhancing our understanding of cancer biology, improving early detection, and guiding the development of targeted therapies that can potentially improve patient outcomes.
subject: Scholarly Peer-reviewed Books
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creator: Parisa Nemati
creator: Amirreza Khalaji
creator: Yasamin Rajabloo
creator: Mohammad Hossein Kazemi
creator: Shadi Nouri
creator: Sohameh Mohebbi
creator: Kimia Karimi Taheri
creator: Amirali Azimi
creator: Fatemeh-sadat Tabatabaei
creator: Sima Aminoleslami
creator: Fatemeh Kazemi
creator: Yasamin Khani
creator: Yasamin Khosravaninezhad
creator: Maryam Damiri
creator: Maryam Ahmadyan
creator: Sheida Mehrani
creator: Ali Jahanshahi
creator: Shila Taherlou
creator: Azadeh Taherlou
creator: Reza Dalvandi
creator: Morteza Alipour
creator: Sarina Azimian Zavareh
creator: Mohammad Sabouri
creator: Seyyed-Ghavam Shafagh
creator: Atefeh Hashemi
creator: Hamidreza Samadpour
creator: Sareh Salarinejad
creator: Farid Farahani Rad
creator: Mehdi Dadpour
creator: Saba Dangpiaei
creator: Mohammad Sharif Sharifani
creator: Yasaman Hadi
creator: Amirmohammad Rezaei
creator: Vida Niakosari
creator: Sepideh Sadat Babaei
creator: Azadeh Rezaeirad
creator: Sara Hosseinmirzaei
creator: Ahmad Abbaszadeh
creator: Lida Zare Lahijan
creator: Amirhossein Rigi
creator: Hamed Sabzehie
creator: Behnoosh Rafieyan
creator: Babak Goodarzy
creator: Yasaman Ghodsi Boushehri
creator: Soheil Bolandi
creator: Mina Goudarzi
creator: Seyed Mobin Tafreshi
creator: Amin Kadkhodaei
creator: Niloufar Jabbari
creator: Mohammadhossein Sadeghi
creator: Masoud Sanati
creator: Maryam Azimi
creator: Yasaman Niakan
creator: Niloofar Khansari Nejad
rights: Copyright (c) 2024 Kindle
date: 2024-10-03
publication date: 2024-10-03
starting page: 1
ending page: 173

AI Chatbots and Telemedicine in Cancer Care: Supporting Patients and Enhancing Communications
type: item
description: AI chatbots and telemedicine are revolutionizing cancer care by providing support to patients and enhancing communication between them and their healthcare providers. AI chatbots use natural language processing (NLP) and machine learning to engage with patients, offering tailored information, emotional support, and assistance in managing treatment plans. For example, they can explain complex medical information, help monitor symptoms, and provide reminders for medication adherence, making patients feel more informed and involved in their care. Telemedicine complements AI chatbots by allowing patients to connect with their healthcare providers remotely, eliminating geographical barriers and reducing the need for frequent hospital visits. This is particularly beneficial for cancer patients who require ongoing monitoring and follow-up care. Through virtual consultations, patients can discuss treatment progress, report side effects, and adjust care plans as needed, fostering a collaborative approach to care. The integration of AI chatbots and telemedicine enhances communication by facilitating a continuous and accessible support system. Patients can access information and guidance at any time, reducing anxiety and improving their overall experience. Additionally, healthcare providers can use data collected through chatbots and telemedicine platforms to make informed, timely decisions about patient care. Together, AI chatbots and telemedicine offer a more efficient, patient-centered approach to cancer care, ultimately improving outcomes and quality of life.
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creator: Mohammad-Soroush Khorsand
creator: Shahin Heidari
creator: Roya Darbani
creator: Yousef Erfani Karimzadeh Tosi
creator: Mohammad Hossein Pourasad
creator: Yasamin Rajabloo
creator: Mahdi Babaei
creator: Shadi Nouri
creator: Amirali Azimi
creator: Fatemeh-sadat Tabatabaei
creator: Mina Afra
creator: Mahtab Mirbolook
creator: Mostafa Talebi
creator: Mohammad Mehdi Atarod
creator: Maryam Ahmadyan
creator: Sara Zare
creator: Sepideh Hassanpour Khodaei
creator: Shima Moradian-Lotfi
creator: Amirhossein Esfahani
creator: Golbarg Saremi
creator: Azadeh Bagheri
creator: Amirhossein Salmannezhad
creator: Hamed Ghorbani
creator: Kamran Sheikhi
creator: Mohammad Sabouri
creator: Mahrokh Janmohamadi
creator: Lida Zare Lahijan
creator: Behnaz Dalvandi
creator: Reza Dalvandi
creator: Seyed Mohammad Shahab Mirabedini
creator: Nasim Razavi
creator: Sara Moghimi
creator: Ahmad Abbaszadeh
creator: Soroush Najdaghi
creator: Ebrahim Evazi
creator: Ehsan Ranjbar
creator: Delaram Narimani Davani
creator: Morteza Alipour
creator: Mohammad Yahyaei Feriz Hendi
creator: Ghazal Sadat Tooyserkani
creator: Mahyar Noorbakhsh
creator: Elham Niknejad
creator: Ariyan Nazemi
creator: Tina Taherzadeh Amlashi
creator: Houman Mazaheri
creator: Shamimeh Arabgol
creator: Amirreza Mohammadnejad
creator: Maryam Alaei
creator: Babak Goodarzy
creator: Dorsa Zareie
creator: Hamed Sabzehie
creator: Setareh Hedayati Emami
creator: Roozbeh Roohinezhad
creator: Yasamin Moradi
creator: Parham Heidari
creator: Asal Salehi
creator: Sadegh Bagherzadeh
creator: Maryam Azimi
creator: Mahfam Alijaniha
creator: Sanaz Riahi
creator: Amirhossein Rigi
rights: Copyright (c) 2024 Kindle
date: 2024-09-19
publication date: 2024-09-19
starting page: 1
ending page: 205

Complementary and Alternative Medicine (CAM)
type: item
description: Complementary and Alternative Medicine (CAM) encompasses a diverse array of practices and therapies not typically part of conventional medical care. CAM includes natural products, mind-body practices, and alternative medical systems. Natural products comprise herbal remedies, vitamins, and minerals. These are often used to complement conventional treatments or as standalone therapies. Examples include ginseng, which is believed to boost energy and improve overall health, and St. John's Wort, often used for depression. Mind-body practices are based on the idea that the mind can influence the body in powerful ways. Techniques such as meditation, yoga, acupuncture, and Tai Chi aim to enhance mental well-being and, consequently, physical health. These practices have been shown to reduce stress, improve mood, and alleviate symptoms of various conditions, from chronic pain to cardiovascular diseases. Alternative medical systems include Ayurveda, Traditional Chinese Medicine (TCM), and homeopathy. Ayurveda, originating from India, uses diet, herbal treatments, and yogic breathing to treat illnesses. TCM includes acupuncture, herbal medicine, and exercises like Qigong. Homeopathy involves highly diluted substances intended to trigger the body's natural healing processes. CAM is increasingly being integrated into conventional medical practice as evidence of its benefits grows. While not all CAM practices are supported by scientific evidence, many people find them beneficial for enhancing quality of life, managing chronic conditions, and promoting overall well-being. As research continues, CAM's role in healthcare is likely to expand, offering more holistic treatment options for patients.
subject: Scholarly Peer-reviewed Books
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creator: Fatemeh Taheri
creator: Masoud Farrokhi
creator: Yasamin Rajabloo
creator: Nasim Razavi
creator: Elham Shirdel
creator: Mohammad Hosseini Hooshiar
creator: Pouran Varvani Farahani
creator: Zahra Yazdani
creator: Sara Hosseinmirzaei
creator: Samineh Esmaeilzadeh
creator: Shamimeh Arabgol
creator: Sephora Khandan
creator: Michael Khorsandi
creator: Nikoo Emtiazi
creator: Farshad Riahi
creator: Kamyar Khorsand
creator: Aria Sadeghian
rights: Copyright (c) 2024 Kindle
date: 2024-08-04
publication date: 2024-08-04
starting page: 1
ending page: 193

Nanomedicine: Technologies and Applications
type: item
description: Nanomedicine is an innovative field that merges nanotechnology with medicine, aiming to enhance diagnosis, treatment, and prevention of diseases at the molecular level. This interdisciplinary domain leverages the unique properties of nanomaterials, such as their small size, surface reactivity, and ability to interact with biological systems in unprecedented ways. One of the core technologies in nanomedicine is the development of nanoscale drug delivery systems. These systems can improve the efficacy and specificity of therapeutic agents by targeting diseased cells while minimizing side effects. Nanocarriers, such as liposomes, dendrimers, and polymeric nanoparticles, are designed to deliver drugs directly to tumor sites, enhancing cancer treatment outcomes. Another critical application is in diagnostic imaging. Nanoparticles, such as quantum dots and magnetic nanoparticles, can serve as contrast agents, providing high-resolution images of biological tissues and enabling early disease detection. These imaging techniques are pivotal in diagnosing conditions like cancer, cardiovascular diseases, and neurodegenerative disorders. Nanomedicine also encompasses the development of biosensors for real-time monitoring of biomarkers. These sensors can detect minute concentrations of disease-related molecules in bodily fluids, facilitating early diagnosis and personalized treatment plans. Furthermore, regenerative medicine benefits from nanotechnology through the creation of scaffolds that support tissue growth and repair. These nanostructured materials can mimic the extracellular matrix, promoting cell adhesion and proliferation, crucial for tissue engineering and wound healing.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Mehrdad Farrokhi
creator: Fatemeh Taheri
creator: Masoud Farrokhi
creator: Yousef Erfani Karimzadeh Tosi
creator: Erfan Ghadirzadeh
creator: Maedeh Bagheri
creator: Atousa Moghadam Fard
creator: Nasim Razavi
creator: Mahsa Dousti
creator: Marjan Dehdilani
creator: Nikoo Emtiazi
creator: Mahyar Noorbakhsh
creator: Alireza Jamali Kalvanagh
creator: Morteza Alipour
creator: San Khasraw Mohammed Mohammed
creator: Mohammad Hosseini Hooshiar
creator: Michael Khorsandi
creator: Hamed Sabzehie
creator: Farshad Riahi
creator: Kimia Shahbazi
creator: Fatemehzahra Shirzad
creator: Seyedeh Maryam Paranchi
creator: Shamimeh Arabgol
creator: Kamyar Khorsand
creator: Fatemeh Mortazavi Moghadam
creator: Aria Sadeghian
creator: Farid Farahani Rad
creator: Mina Goudarzi
creator: Seyed Mobin Tafreshi
creator: Hournaz Hassanzadeh
rights: Copyright (c) 2024 Kindle
date: 2024-07-23
publication date: 2024-07-23
starting page: 1
ending page: 196

Digital Health and Wearable Technologies
type: item
description: Digital health and wearable technologies represent a transformative wave in healthcare, blending medical advancements with innovative technology to enhance patient care, monitor health conditions, and promote wellness. These technologies encompass a wide range of devices, from fitness trackers and smartwatches to sophisticated medical devices designed for continuous health monitoring. Wearable technologies, such as smartwatches and fitness bands, are equipped with sensors that track various health metrics, including heart rate, steps taken, calories burned, sleep patterns, and even blood oxygen levels. These devices provide real-time data, empowering individuals to make informed decisions about their health and lifestyle. The integration of wearable technology with smartphone applications allows for the seamless transfer and analysis of health data, fostering a proactive approach to personal health management. In the realm of clinical healthcare, wearable technologies are revolutionizing patient monitoring and management. Devices such as continuous glucose monitors and wearable ECGs offer patients and healthcare providers critical insights into chronic conditions, enabling timely interventions and personalized treatment plans. Remote patient monitoring, facilitated by these wearables, reduces the need for frequent hospital visits, thus improving patient convenience and reducing healthcare costs. Moreover, the data collected from wearable devices contribute to a vast repository of health information, advancing research and development in preventive medicine and chronic disease management. As digital health and wearable technologies continue to evolve, they hold the promise of more efficient, personalized, and accessible healthcare, ultimately enhancing the quality of life for individuals worldwide.
subject: Scholarly Peer-reviewed Books
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subject: Kindle Books
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creator: Shiva Karimian
creator: Fatemeh Taheri
creator: Mehrdad Farrokhi
creator: Masoud Farrokhi
creator: Ziba Bayat
creator: Sayed Alireza Mousavi Zadeh
creator: Erfan Ghadirzadeh
creator: Seyyed Amirreza Abdollahi
creator: Mahmonir Bayanati
creator: Artin Ahmadpour
creator: Atefeh Nazary
creator: Shahram Samadi
creator: Mahyar Noorbakhsh
creator: Shila Taherlou
creator: Azadeh Taherlou
creator: Mohamadreza Safari
creator: Armin Sedighi
creator: Zohreh Molaei
creator: Mohammad Toussi
creator: Fatemeh Honarvar
creator: Mohammad Sabouri
creator: Fatemeh Mortazavi Moghadam
creator: Amir Askarinejad
creator: Horrieh Abbasmofrad
creator: Morteza Alipour
creator: Nahid Abbasian
creator: Nikoo Emtiazi
creator: Mohammad Hosseini Hooshiar
creator: Michael Khorsandi
creator: Kamyar Khorsand
creator: Farshad Riahi
creator: Hournaz Hassanzadeh
rights: Copyright (c) 2024 Kindle
date: 2024-06-23
publication date: 2024-06-23
starting page: 1
ending page: 240

The AI Diagnostician: Improving Medical Diagnosis with Artificial Intelligence
type: item
description: The integration of artificial intelligence (AI) into the field of medical diagnostics represents a revolutionary advancement in healthcare. AI diagnosticians, powered by sophisticated algorithms and vast datasets, are transforming how diseases are detected and diagnosed, offering potential improvements in accuracy, efficiency, and accessibility. One of the primary advantages of AI in medical diagnosis is its ability to analyze and interpret large volumes of data rapidly. Traditional diagnostic processes, which rely heavily on human expertise, can be time-consuming and prone to errors. In contrast, AI systems can process complex medical data, including medical imaging, laboratory results, and patient histories, in a fraction of the time. For instance, AI algorithms have demonstrated remarkable proficiency in interpreting radiological images, often matching or surpassing the diagnostic accuracy of experienced radiologists in detecting conditions such as cancer, fractures, and neurological disorders. Moreover, AI diagnosticians excel in identifying patterns and correlations that may be overlooked by human clinicians. Machine learning models can be trained on extensive datasets to recognize subtle indicators of disease, leading to earlier and more accurate diagnoses. This capability is particularly beneficial in diagnosing rare diseases and conditions with ambiguous symptoms, where traditional diagnostic methods might falter. AI also enhances the accessibility of medical diagnosis. In regions with limited access to healthcare professionals, AI-powered diagnostic tools can provide essential support. For example, AI applications in telemedicine enable remote diagnosis and consultation, bridging the gap between patients and medical expertise. This democratization of diagnostic services has the potential to improve healthcare outcomes in underserved communities globally.
subject: Scholarly Peer-reviewed Books
  topic: section
subject: Kindle Books
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subject: Array
  topic: keywords
subject: Array
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creator: Mehrdad Farrokhi
creator: Fatemeh Taheri
creator: Ehsan Adibnia
creator: Saba Mehrtabar
creator: Zahra Rassaf
creator: Seyed Hamed Tooyserkani
creator: Yasamin Rajabloo
creator: Ghazal Sadat Tooyserkani
creator: Zohreh Ranjbar
creator: Erfan Hashemi
creator: Mohammad-Soroush Khorsand
creator: Sima Aminoleslami
creator: Hamed Sabzehie
creator: Shila Taherlou
creator: Seyede Mahshad Moosavi
creator: Mansoureh Fatahi
creator: Azadeh Taherlou
creator: Erfan Kohansal
creator: Azadeh Rezaeirad
creator: Mohammadhossein Kardan
creator: Fatemeh Boroumandfar
creator: Behzad Garousi
creator: Mahsa Azarshab
creator: Alireza Mojarrad
creator: Haniyeh Ghasrsaz
creator: Tara Mahmoodi
creator: Farid Farahani Rad
creator: Donya Pourkand
creator: Asieh Zohrei
creator: Nikoo Emtiazi
creator: Amir Askarinejad
creator: Khatere Roozbehi
creator: Dorsa Beheshtiparvar
creator: Alireza Daneshvar
creator: Kimia Daneshvar
creator: Arman MomeniAmjadi
creator: Kamyar Khorsand
creator: Parnian Pour Bahrami
creator: Mohammad Hosseini Hooshiar
creator: Maryam Ahmadyan
creator: Hournaz Hassanzadeh
creator: Seyed Mobin Tafreshi
creator: Michael Khorsandi
creator: Mohsen Motavaselian
creator: Mina Goudarzi
creator: Farshad Riahi
creator: Masoud Farrokhi
rights: Copyright (c) 2024 Kindle
date: 2024-05-23
publication date: 2024-05-23
starting page: 1
ending page: 219