Tariq Raseen, Voth Elida, Khanna Sahil
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN.
Mayo Clin Proc Digit Health. 2024 Mar 28;2(2):177-180. doi: 10.1016/j.mcpdig.2024.02.004. eCollection 2024 Jun.
Navigating clinical guidelines can be complex for real-time health care decision making. Our study evaluates the chat generative prerained transformer (ChatGPT)-4 in improving responses to clinical questions by integrating guidelines on infection and colon polyp surveillance. We assessed ChatGPT-4's responses to questions before and after guideline integration, noting a clear improvement in accuracy. ChatGPT-4 provided guideline-aligned answers consistently. Further analysis showed its ability to summarize information from conflicting guidelines, highlighting its utility in complex clinical scenarios. The findings suggest that large language models such as ChatGPT-4 can enhance clinical decision making and patient education by providing quick, conversational, and accurate responses. This approach opens a path for using artificial intelligence to deliver reliable responses in health care, supporting clinicians in real-time decision making and improving patient care.
对于实时医疗决策而言,遵循临床指南可能很复杂。我们的研究评估了聊天生成预训练变换器(ChatGPT)-4在通过整合感染和结肠息肉监测指南来改善对临床问题的回答方面的表现。我们评估了ChatGPT-4在整合指南前后对问题的回答,注意到准确性有明显提高。ChatGPT-4始终提供与指南一致的答案。进一步分析表明,它有能力总结相互冲突的指南中的信息,凸显了其在复杂临床场景中的实用性。研究结果表明,像ChatGPT-4这样的大语言模型可以通过提供快速、对话式且准确的回答来增强临床决策和患者教育。这种方法为利用人工智能在医疗保健中提供可靠回答开辟了一条道路,支持临床医生进行实时决策并改善患者护理。