评估高风险非ST升高急性冠状动脉综合征患者使用人工智能和计算机断层扫描进行冠状动脉扫描的需要
Aurelien Cagnina1, Adil Salihu1, David Meier1
1Cardiology Department, University Hospital of Lausanne and University of Lausanne, Rue de Bugnon 46, Lausanne, 1011, Switzerland.
The international journal of cardiovascular imaging
|November 8, 2024
概括
在指导急性冠状动脉综合征 (ACS) 患者的侵入性冠状动脉血管学 (ICA) 决策方面,ChatGPT显示出前景. 这种人工智能工具的准确率达到了86%,这可能会减少不必要的程序.
科学领域:
- 心脏病学 心脏病学
- 人工智能在医学中的应用
- 医学诊断 医学诊断 医学诊断
背景情况:
- 高风险非ST升高的急性冠状动脉综合征 (NSTE-ACS) 需要对侵入性冠状动脉血管学 (ICA) 进行仔细评估.
- 准确的决策对于ICA至关重要,以避免不必要的侵入性手术,并确保对重大冠状动脉疾病及时进行干预.
研究的目的:
- 评估聊天生成预训练变压器 (ChatGPT) 在指导高风险NSTE-ACS患者的ICA决策中的有效性.
- 用标准临床数据和冠状动脉计算机断层扫描血管学 (CCTA) 发现来评估ChatGPT的准确性.
主要方法:
- 一个潜在的,多中心的,双盲试验的子研究,涉及高风险的NSTE-ACS患者.
- 患者在ICA之前接受了CCTA以进行比较性病变分析.
- ChatGPT分析了包括心电图,热素水平和CCTA结果在内的临床细节,以推ICA的必要性.
主要成果:
- 在推ICA时,ChatGPT的整体准确率为86%.
- 人工智能实现了95%的灵敏度和64%的特异性,用于检测显著的冠状动脉病变.
- 积极和消极的预测值分别为87%和84%.
结论:
- 聊天GPT显示潜在的作为一个有效的工具,以协助ICA决策高风险NSTE-ACS患者.
- 这些发现表明,人工智能可以帮助减少不必要的侵入性手术的数量.
- 建议与更大,多样化的队伍进行进一步的研究,以完善AI在临床决策支持中的作用.
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