1st Edition
Large Language Models (LLMs) for Healthcare A Practical Guide to Their Process and Evaluation
Chapter 1: Introduction to Large Language Models for Healthcare
Chapter 2: Who makes the BEST Expert
Chapter 3: Understanding the Technology Behind LLMs
Chapter 4: The Current State of LLMs in Healthcare
Chapter 5: The Data that Feeds LLMs
Chapter 6: Basic Prompt Engineering
Chapter 7: Prompt Engineering vs Finetuning
Chapter 8: Developing LLMs for Healthcare Applications
Chapter 9: Evaluating LLM Vendors Maturity for Healthcare
Chapter 10: Bias in LLMs and Its Implications for Healthcare
Chapter 11: Ensuring Compliance and Ethical Use
Chapter 12: LLMs in Clinical Decision Support Systems
Chapter 13: Patient Engagement and LLMs
Chapter 14: Training and Educating Healthcare Professionals on LLMs
Chapter 15: Security and Privacy Concerns with Healthcare LLMs
Chapter 16: The Role of Interdisciplinary Teams in LLM Projects
Chapter 17: Implementing LLM Solutions
Chapter 18: Integration with Electronic Health Records (EHR)
Chapter 19: Measuring the Impact of LLMs in Healthcare
Chapter 20: Looking Ahead: The Future of Healthcare with LLMs
References
Biography
Jeremy Harper is President of Owl Health Works, a consulting firm providing quality management, health informatics, and business services for their clients. He has 20 years of healthcare industry experience including academic medical centers, community hospitals, and software vendors. As an executive, his responsibilities have included planning, implementation, and management of deployments and enterprise-enhancing initiatives. He is an authority for best practices in artificial intelligence/machine learning, business strategy, data management, transformations, turnarounds, and organization growth strategies.
