Enhancing Large Language Models for Improved Accuracy and Safety in Medical Question Answering: Comparative Study.

ABSTRACT:

Background

Large language models (LLMs) offer the potential to improve virtual patient-physician communication and reduce health care professionals' workload. However, limitations in accuracy, outdated knowledge, and safety issues restrict their effective use in real clinical settings. Addressing these challenges is crucial for making LLMs a reliable health care tool.

Objective

This study aimed to evaluate the efficacy of Med-RISE, an information retrieval and augmentation tool, in comparison with baseline LLMs, focusing on enhancing accuracy and safety in medical question answering across diverse clinical domains.

Methods

This comparative study introduces Med-RISE, an enhanced version of a retrieval-augmented generation framework specifically designed to improve ques

SUBMITTER: Wang D 

PROVIDER: S-EPMC12709156 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature