Large Language Models (LLMs) for Healthcare

A Practical Guide to Their Process and Evaluation

Jeremy Harper

• Publisher: Productivity Press
• Year: 2025
• Topic: Business
• eBook ISBN:
  9781040381984
• Subtopic: Gestione dell'informazione
• Index: Business

In today's rapidly evolving healthcare environment, one technology stands at the forefront of innovation: large language models (LLMs). Far more than a fleeting hype, LLMs represent a foundational shift in how healthcare professionals interact with and derive value from data. From simplifying clinical note-writing to supporting patient engagement and enhancing administrative processes, LLMs have the power to transform nearly every corner of the healthcare ecosystem. In Large Language Models (LLMs) for Healthcare, Jeremy Harper shines a spotlight on this transformative potential. With clarity and practicality, he explores how these advanced artificial intelligence (AI) tools can reshape clinical workflows, optimize administrative tasks, and ultimately create a more responsive, patient-centered model of care. Over the course of this book, you will discover new opportunities—learn how LLMs can reduce manual documentation burdens, provide intelligent summaries of complex patient histories, and offer real-time translations of clinical jargon; understand the fundamentals—grasp what LLMs are, how they work, and why they can handle vast amounts of clinical text more effectively than previous AI tools; examine key use cases—from automated billing support and smart note generation to patient triage and ethical telehealth consultations; address risks and realities—gain insight into challenges such as "hallucinations," inherent bias, and the critical importance of patient privacy; plan for implementation—explore strategies for prompt engineering, fine-tuning, and rigorous evaluation of LLM solutions; and envision the future – glimpse how LLMs might revolutionize healthcare through enhanced back-office operations and cutting-edge clinical decision support.

Table of contents

• Cover
• Half Title
• Title
• Copyright
• Dedication
• Contents
• 1 Introduction to Large Language Models for Healthcare
• 2 Who Makes the BEST Expert
• 3 Understanding the Technology behind LLMs
• 4 The Current State of LLMs in Healthcare
• 5 The Data That Feeds LLMs
• 6 Basic Prompt Engineering
• 7 Prompt Engineering versus Fine-Tuning
• 8 In-house Development of LLMs for Healthcare Applications
• 9 Evaluating LLM Vendors’ Maturity for Healthcare
• 10 Bias in LLMs and Its Implications for Healthcare
• 11 Ensuring Compliance and Ethical Use
• 12 LLMs in Clinical Decision Support Systems
• 13 Patient Engagement and LLMs
• 14 Training and Educating Healthcare Professionals on LLMs
• 15 Security and Privacy Concerns with Healthcare LLMs
• 16 The Role of Interdisciplinary Teams in LLM Projects
• 17 Implementing LLM Solutions
• 18 Integration with Electronic Health Records
• 19 Measuring the Impact of LLMs in Healthcare
• 20 Looking Ahead: The Future of Healthcare with LLMs
• Index