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Adil Salihu¹, David Meier¹, Nathalie Noirclerc¹

¹Department of Cardiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland.

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology

|April 17, 2024

概括

人工智能 (AI),特别是大型语言模型 (LLM),在支持多学科心脏团队 (HTs) 进行膜心脏病管理方面表现有前途. 聊天GPT与HT决策达成77%的共识,有助于临床决策.

科学领域:

心脏病学心脏病学
人工智能在医学中的应用
医疗信息学医疗信息学

背景情况:

多学科心脏团队 (HTs) 对于管理心脏膜疾病至关重要.
后勤方面的挑战可能会阻碍医疗保健人员对患者数据进行全面的评估,这可能会影响医疗保健.
提高HT的效率和决策对于最佳的患者结果至关重要.

研究的目的:

研究人工智能 (AI) 的潜力,特别是大型语言模型 (LLM),以提高HT效率.
评估AI在改善HTs内的临床决策过程的能力.
评估人工智能产生的建议与专家HT决策的一致性.

主要方法:

在HT会议上提出的重症大动脉狭窄病例患者数据的回顾性分析.
使用OpenAI的GPT-4来处理14个关键变量的标准化问卷.
将人工智能产生的治疗决策与人类多学科心脏团队的治疗决策进行比较.

主要成果:

这项研究分析了150名患者的数据.
聊天GPT显示,与HT的最终决定达成一致率为77%.
协议因治疗而有所不同:90%用于透气管植入,65%用于手术置换,65%用于医疗管理.

结论:

大型语言模型 (LLM) 提供了一个显著的机会,可以在膜心脏病中改进HT决策.
像ChatGPT这样的AI工具可以作为一种有价值的故障保护,标记差异以供进一步审查.
需要进一步的研究来充分整合AI到HT工作流程中,以加强临床决策支持.

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