人工智能增强心电图用于检测心脏粉症的后期开发性能和验证
David M Harmon1,2, Kathryn Mangold2, Abraham Baez Suarez2
1Department of Internal Medicine, Mayo Clinic School of Graduate Medical Education, Rochester, Minnesota, USA.
JACC. Advances
|April 19, 2024
概括
人工智能 (AI) 电心电图 (ECG) 工具在检测心脏粉症 (CA) 中表现出强的性能. 对于特定的患者子组,如西班牙裔个人和某些心电图模式的患者,需要进一步验证.
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:
- 人工智能 (AI) 之前的应用在心电图 (ECG) 中用于心脏粉症 (CA) 检测.
- 需要在开发后验证AI-ECG性能,考虑到潜在的混因素.
研究的目的:
- 验证AI增强型心电图用于检测CA的开发后性能.
- 评估AI-ECG在各种患者人口统计和临床因素中的表现.
主要方法:
- 在算法开发后 (2019年6月至2022年1月) 鉴定了440名被诊断为CA的患者,这些患者使用了12心电图.
- 与15:1年龄和性别匹配的对照组进行比较 (n=6,600).
- 计算接收器运行特征下的面积 (AUC) 对整体队列和子组的计算.
主要成果:
- 在AI-ECG中,CA检测的AUC为0.84 (95%CI:0.82-0.86),略低于原始研究 (AUC0.91).
- 白人,黑人和"其他"种族的表现一致 (AUC>0.81),西班牙裔患者的表现下降 (AUC 0.66).
- 高AUC (>0.90) 低心电图电压和心脏病发作模式;较低的AUC (0.75-0.76) 左心室缩和左束枝断.
结论:
- AI-ECG在跨年龄,性别,种族和粉样蛋白亚型的CA检测方面表现强.
- 特定小组的验证至关重要,特别是对于左束枝断,左心室缩和多样化的种族群体,由于观察到的性能变化.
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An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
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