Generative Large Language Models in Electronic Health Records for Patient Care Since 2023: A Systematic Review.

ABSTRACT:

Background

Generative Large language models (LLMs) represent a significant advancement in natural language processing, achieving state-of-the-art performance across various tasks. However, their application in clinical settings using real electronic health records (EHRs) is still rare and presents numerous challenges.

Objective

This study aims to systematically review the use of generative LLMs, and the effectiveness of relevant techniques in patient care-related topics involving EHRs, summarize the challenges faced, and suggest future directions.

Methods

A Boolean search for peer-reviewed articles was conducted on May 19^th, 2024 using PubMed and Web of Science to include research articles published since 2023, which was one month after the release of ChatG

SUBMITTER: Du X 

PROVIDER: S-EPMC11370524 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature