用人工智能增强的心电图用于早期评估冠状病毒疾病的严重程度2019年
Yong-Soo Baek1,2,3, Yoonsu Jo4, Sang-Chul Lee4,5
1Division of Cardiology, Department of Internal Medicine, Inha University College of Medicine, Inha University Hospital, 27 Inhang-ro, Jung-gu, Incheon, 22332, Republic of Korea. existsoo@inha.ac.kr.
人工智能增强心电图 (AI-ECG) 显示出预测2019年新冠肺炎疾病 (COVID-19) 严重程度的前景. 这种人工智能工具有助于早期患者风险分层和死亡率预测,改善管理.
科学领域:
- 心脏病学 心脏病学
- 传染性疾病 传染性疾病
- 人工智能在医学中的应用
背景情况:
- 预测2019年冠状病毒病 (COVID-19) 严重程度对于患者管理至关重要.
- 现有的严重性评分系统在准确性和及时应用方面面临挑战.
- 电心电图 (ECG) 提供了一个易于获得的诊断工具.
研究的目的:
- 评估人工智能增强心电图 (AI-ECG) 在预测COVID-19严重性的有效性.
- 将AI-ECG性能与传统的早期预警分数 (EWS) 进行比较.
- 评估AI-ECG与COVID-19患者死亡率的关联.
主要方法:
- 分析了接受心电图的1453名COVID-19患者.
- 一个AI-ECG算法被开发和验证用于严重性预测.
- 性能指标包括曲线下的面积 (AUC),精度,回忆和F1分数.
- 考克斯的比例危险模型被用来评估死亡风险.
主要成果:
- 在预测COVID-19严重程度方面,AI-ECG表现合理 (AUC为0.735和0.734).
- 结合AI-ECG和EWS显示性能有所改善 (AUC为0.833,精度为0.764,回忆为0.747,F1为0.747).
- 人工智能心电图与较高的死亡风险显著相关 (HR 2.019,p=0.014).
结论:
- AI-ECG显示出作为早期预测COVID-19严重程度的工具的潜力.
- 将AI-ECG与EWS集成,可以提高预测能力.
- AI-ECG可以帮助临床医生在早期风险分层和COVID-19患者管理方面提供帮助.
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