Scholarlink

Abstract <p>The development of digital technologies and artificial intelligence is contributing to the evolution of decision support systems in medicine, where there is a growing interest in health recommendation systems (HRSs), which today requires an expansion of the knowledge base concerning the surrounding world to improve the explainability of the recommendations provided. In the paper, the potential of three ChatGPT models (GPT-3.5, GPT-4, and GPT-4o) for generating explanations of cardiovascular risk factors has been evaluated. The results of the analysis show that these models have significant potential to generate understandable, safe, and correct explanations of disease risk factors, which can form the basis for the development of promising HRSs to automate the preparation of medical reports and providing patients with explainable recommendations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Exploring the Potential of Large Language Models to Create Explainable Medical Recommendations

  • 期刊论文

  • 发表日期：

    2025年10月1日

查看全文
  • T. V. Afanasieva,
  • P. V. Platov

摘要

Abstract

The development of digital technologies and artificial intelligence is contributing to the evolution of decision support systems in medicine, where there is a growing interest in health recommendation systems (HRSs), which today requires an expansion of the knowledge base concerning the surrounding world to improve the explainability of the recommendations provided. In the paper, the potential of three ChatGPT models (GPT-3.5, GPT-4, and GPT-4o) for generating explanations of cardiovascular risk factors has been evaluated. The results of the analysis show that these models have significant potential to generate understandable, safe, and correct explanations of disease risk factors, which can form the basis for the development of promising HRSs to automate the preparation of medical reports and providing patients with explainable recommendations.