This book offers a comprehensive exploration into the role of Large Language Models (LLMs) in modern healthcare. It focuses specifically on the lifecycle of LLM deployment in healthcare settings, including transparency, accountability, data privacy, and regulatory compliance to ensure safe and effective use. By bridging the gap between technical artificial intelligence (AI) development and clinical application, this book highlights the critical collaboration between clinicians and data scientists to create representative datasets and fine-tune models for clinical accuracy and interpretability. Real-world challenges such as mitigating bias, managing AI hallucinations, and safeguarding patient confidentiality are explored, alongside strategies for continuous improvement and long-term impact assessment. Key features include: - Case studies illustrating LLM applications in clinical decision support, medical imaging, patient communication, and administrative automation. - In-depth discussion of data privacy, regulatory compliance, and ethical considerations in AI healthcare applications. - Insights into overcoming challenges like bias, hallucinations, and interoperability with existing health information systems. - How LLMs could revolutionize patient care in future, including operational efficiency and personalized medicine. This book is an essential resource for clinicians, healthcare executives, technologists, data scientists, and students seeking to harness the power of LLMs to improve patient outcomes and streamline healthcare delivery.

Table of Contents:
Preface List of Contributors Editor Bios Chapter 01 Large Language Models in Clinical Application Homayoun Safarpour, Amirfarhad Farhadi, Martin Cunneen, György Molnár, Eniko Nagy Chapter 02 Administrative Efficiency: Providing Healthcare Operations Alireza Taheri, Amirfarhad Farhadi, Azadeh Zamanifar, Amirmohammad Mataji Chapter 03 LLMs in drug discovery, clinical trial analysis, and medical literature review Sina Abbaskhani, Deniz NoorMohammadzadehMaleki, Amirfarhad Farhadi, and Azadeh Zamanifar Chapter 04 LLMs For Personalaized Medicine and Treatment planning Amirfarhad Farhadi, and Nasser Mozayeni Chapter 05 The Large Language Models for Public Health Surveillance and Outbreak Arezou Naghib, Farhad Soleimanian Gharehchopogh, and Parisa Tavana Chapter 06 The Role of Large Language Models in Delivering Artificial Intelligence-Based Psychological Interventions and Therapies Arezou Naghib, Farhad Soleimanian Gharehchopogh, and Azadeh Zamanifar Chapter 07 Explainable AI (XAI): Making LLM Decisions Transparent and Trustworthy Amirfarhad Farhadi, Azadeh Zamanifar, Fouad Bahrpeyma Chapter 08 Ethical Implications for LLMs Mohammad Saleh, and Azadeh Tabatabaei Chapter 09 Limitations of Large Language Models in Healthcare Systems Farshid Babapour Mofrad , and Midya Yousefzamani Chapter 10 Future Trends and Innovations in Healthcare Systems Using LLMs Kiana Pilevar Abrisham, and Khalil Alipour