通过使用人工智能解释广泛复杂的心动节拍
Benjamin J W Chow1, Najmeh Fayyazifar2, Saad Balamane3
1Department of Medicine (Cardiology), University of Ottawa Heart Institute, Ottawa, Ottawa, Ontario, Canada; Department of Radiology, University of Ottawa, Ottawa, Ontario, Canada.
人工智能 (AI) 现在可以以与电生理学专家相比的准确性解读宽复杂性心跳动脉图 (WCT) 电心图 (ECG). 这种人工智能工具通过提高心电图解读速度和准确性来提高患者护理的潜力.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
背景情况:
- 人工智能 (AI) 具有提高医学诊断速度和准确性的潜力.
- 通过心电图 (ECG) 诊断广复合性心力衰竭 (WCT) 是一个关键的临床挑战.
研究的目的:
- 开发一个AI算法来解释WCT心电图.
- 将人工智能算法的诊断准确度与心脏病学家进行比较.
主要方法:
- 一个卷积神经网络 (CNN) 是使用修改的微分架构搜索开发的.
- 人工智能模型在3131个WCT ECG上进行了训练和验证,并在199个ECG上进行了测试.
- 人工智能的表现与电生理学 (EP) 和非EP心脏病学家的表现进行了比较.
主要成果:
- 人工智能实现了93.0%的准确性,91.9%的灵敏度,超过了非EP心脏病学家.
- 人工智能的表现与EP心脏病专家 (92.5%的准确率) 相当.
- 人工智能解释时间比人类心脏病学家 (3.116.6秒) 快得多 (0.0092秒).
结论:
- 人工智能在诊断来自心电图的WCT方面表现出比非EP心脏病学家更高的准确性,与EP心脏病学家的准确性相似.
- 人工智能辅助的心电图解释有望改善患者护理和诊断效率.
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