Application of Large Language Models in Complex Clinical Cases: Cross-Sectional Evaluation Study.

ABSTRACT:

Background

Large language models (LLMs) have made significant advancements in natural language processing (NLP) and are gradually showing potential for application in the medical field. However, LLMs still face challenges in medicine.

Objective

This study aims to evaluate the efficiency, accuracy, and cost of LLMs in handling complex medical cases and to assess their potential and applicability as tools for clinical decision support.

Methods

We selected cases from the database of the Department of Cardiothoracic Surgery, the Third Affiliated Hospital of Sun Yat-sen University (2021-2024), and conducted a multidimensional preliminary evaluation of the latest LLMs in clinical decision-making for complex cases. The evaluation included measuring the time taken for the LLM

SUBMITTER: Huang Y 

PROVIDER: S-EPMC12501899 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature