Large Language Models in Healthcare: Opportunities, Applications, and Challenges
暫譯: 醫療保健領域的大型語言模型：機會、應用與挑戰

This book offers a timely introduction to the rapidly evolving role of artificial intelligence in modern healthcare. Designed for a broad audience, including students, practitioners, researchers, and librarians, it provides clear explanations and a solid conceptual foundation for understanding current advances and anticipating future breakthroughs in healthcare AI. A central focus of the book is the transformative rise of large language models (LLMs). These models now influence clinical documentation, decision support, knowledge extraction, and patient communication. While showcasing their potential to enhance healthcare delivery, the book also examines the concerns they raise, including ethical risks, transparency, fairness, and the significant resources required to deploy them safely.

Bringing together contributions from international experts, the book offers a comprehensive overview of how LLMs are being applied across medical imaging, diagnostics, multimodal data analysis, and clinical workflows. It also highlights the practical challenges of fine-tuning and integrating these systems into real-world clinical environments.

Importantly, the book provides thought-provoking insights on trust, accountability, and responsible AI, making it an essential reference for anyone seeking to navigate the opportunities and challenges of LLM-driven healthcare.

Key Features:

- A timely comprehensive coverage of LLMs in healthcare.

- Contributions from a global network of authors from ten different countries.

- Insightful discussions on ethics, trust, and hallucinations in LLMs.

- Real world case studies and fills the gap between technical AI research and implementation.

- Value for a broad audience, serving as an essential resource for researchers, clinicians, policymakers, and advanced students.

Dr. Hazrat Ali is a Lecturer in Artificial Intelligence at the University of Stirling, United Kingdom. He is a senior member of the IEEE and Associate Editor at Wiley Applied, Nature Scientific Reports journals, and leads multiple research initiatives in Healthcare AI.

Mubashir Husain Rehmani (M'14-SM'15, SFHEA) received the Ph.D. degree from the University Pierre and Marie Curie, Paris, in 2011. He is currently working as Lecturer in the Department of Computer Science, Munster Technological University, Ireland. He is the recipient of Highly Cited Researcher award four times in 2020, 2021, 2022, and 2025 by Clarivate, USA.