Large Language Models (LLMs) for Healthcare: A Practical Guide to Their Process and Evaluation

This book starts with discussions over how large language models are used in healthcare and the opportunities we have to change portions of the healthcare paradigm. There are amazing opportunities to save both time as a business unit as well as improve patient experiences. Large language models (LLMs) are machine learning models that can comprehend and generate human language text. They work by analyzing massive data sets of language. They can be used for text generation, a form of generative AI, by taking an input text and repeatedly predicting the next token or word. Some notable LLMs are OpenAI''s GPT series of models, Google''s PaLM and Gemini, and Meta''s LLaMA family of open-source models to name a few.This book starts with discussions over how large language models are used in healthcare and the opportunities we have to change portions of the healthcare paradigm. There are amazing opportunities to save both time as a business unit as well as improve patient experiences. The book then continues with broad-reaching descriptions of what is reasonable to expect and not expect a large language model to be able to accomplish. The author also discusses why large language models are important and how they are going to change the industry with a detailed description of large language models. He brings a highly technical discussion of vector maths and interprets it to something that non-specialists can understand. He also explains how large language model transformers work and why we’ve seen success in image generation, language generation, and implementation. Also provided is a discussion of the planning and strategy for implementing LLM solutions and recommendations for measuring their impact. Finally, the book discusses future trends in healthcare LLMs, emerging technologies and their potential impact in the coming years and decades.

• | Author: Jeremy Harper
• | Publisher: Taylor & Francis Ltd
• | Publication Date: Sep 01, 2025
• | Number of Pages:
• | Language:
• | Binding: Paperback / softback
• | ISBN-13: 9781032887289
• | ISBN-10: 1032887281