在成年人中以人工智能支持的8导电图检测心房隔膜缺陷:一种新的诊断工具
Qiushi Luo1, Hongling Zhu1, Jiabing Zhu2
1Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Frontiers in cardiovascular medicine
|November 29, 2023
概括
使用8导电心电图 (ECG) 的人工智能 (AI) 模型在检测成人心房隔膜缺陷 (ASD) 中显示出高准确性. 这种支持人工智能的心电图方法为早期ASD诊断和临床决策提供了有前途的潜力.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 耳前隔膜缺陷 (ASD) 呈现出特征但未确定的心电图 (ECG) 图案.
- 目前对ASD的诊断方法有限,人工智能在其他心血管疾病检测方面表现有前途.
- 需要改进ASD的诊断工具,特别是在成年人群中.
研究的目的:
- 开发和验证一个支持人工智能的8导电心电图系统,用于检测成年人的心房隔膜缺陷 (ASD).
- 通过使用心电图数据,评估AI模型在区分ASD与正常心脏结构方面的诊断性能.
- 探索AI在非侵入性ASD检测中的临床实用性和潜力.
主要方法:
- 使用带有残余网络架构的卷积神经网络 (CNN) 来分析8导电心电图数据.
- 人工智能模型在一个单一医院的526例自闭症病例和2,124例对照数据集上进行了训练和验证.
- 外部验证是使用武汉中央医院的50例ASD病例和46例对照进行的,采用了10倍交叉验证方法.
主要成果:
- 人工智能模型在内部数据集上实现了高性能,准确度为0.97,ASD检测AUC为0.99.
- 外部测试显示出强大的性能,准确度为0.82,AUC为0.87.
- 在ASD和正常组之间观察到心电图特征的统计学上显著差异 (p < 0.05).
结论:
- 以人工智能为动力的8导电图分析可以有效地检测成年人的心房隔膜缺陷,具有很高的诊断准确性.
- 这种人工智能支持的方法对ASD的早期检测具有显著的临床前景.
- 在ECG中使用较少的线索对便携式设备来说是有利的,可能会带来巨大的经济和社会效益.
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Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
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Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
606