Optimization of hepatological clinical guidelines interpretation by large language models

Summary

The article discusses the integration of Large Language Models (LLMs) like GPT-4 into clinical decision support systems (CDSSs), to improve healthcare by utilizing Retrieval Augmented Generation (RAG) and natural language processing. It emphasizes the need for guidelines in text format to facilitate accurate output by LLMs, while also highlighting the limitations in non-text source interpretation. The tags reflect the technologies and fields involved in this advancement, including AI models by OpenAI, deep learning, prompt engineering, and the potential for reaching artificial general intelligence (AGI) through such applications.