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Full Description
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.
Contents
Preface
List of Contributors
Editor Bios
Chapter 01 Large Language Models in Clinical Application
Homayoun Safarpour, Amirfarhad Farhadi, Martin Cunneen, György Molnár, Enikő 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
