Automated identification of innocent Still's murmur using a convolutional neural network.
Automated identification of innocent Still's murmur using a convolutional neural network.
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DOI：
10.3389/fped.2022.923956
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发表时间：
2022
影响因子：
2.6
通讯作者：
Doroshow, Robin W.
中科院分区：
文献类型：
--
作者：
Shekhar, Raj;Vanama, Ganesh;John, Titus;Issac, James;Arjoune, Youness;Doroshow, Robin W.
关键词：
斯蒂尔杂音是儿童期最常见的心脏杂音。听诊是鉴别这种杂音为良性的主要临床工具。尽管儿科心脏病专家经常执行这项任务，但初级保健提供者在区分Still杂音与真正心脏病杂音方面不太成功。这导致了大量的儿童与斯蒂尔杂音被称为儿科心脏病专家。开发一种计算机算法，可以帮助初级保健提供者在护理点识别无辜的斯蒂尔杂音，以大大减少过度转诊。该研究包括斯蒂尔杂音、病理性杂音、其他无害杂音和正常杂音（即，非杂音）心音的1,473名儿科患者使用商业电子听诊器记录。由儿科心脏病专家提供的附带临床诊断的记录用于训练和测试基于卷积神经网络的算法。对比分析表明，仅使用胸骨左下缘处记录的杂音的算法实现了最高的准确性。所开发的算法识别Still杂音，对于默认决策阈值具有90.0%的灵敏度和98.3%的特异性。受试者工作特征曲线下面积为0.943。我们开发的算法可以高精度地识别斯蒂尔杂音。使用这种方法，该算法可以帮助减少不必要的儿科心脏病专家转诊率和使用超声心动图检查常见的良性发现。
Still's murmur is the most prevalent innocent heart murmur of childhood. Auscultation is the primary clinical tool to identify this murmur as innocent. Whereas pediatric cardiologists routinely perform this task, primary care providers are less successful in distinguishing Still's murmur from the murmurs of true heart disease. This results in a large number of children with a Still's murmur being referred to pediatric cardiologists. To develop a computer algorithm that can aid primary care providers to identify the innocent Still's murmur at the point of care, to substantially decrease over-referral. The study included Still's murmurs, pathological murmurs, other innocent murmurs, and normal (i.e., non-murmur) heart sounds of 1,473 pediatric patients recorded using a commercial electronic stethoscope. The recordings with accompanying clinical diagnoses provided by a pediatric cardiologist were used to train and test the convolutional neural network-based algorithm. A comparative analysis showed that the algorithm using only the murmur sounds recorded at the lower left sternal border achieved the highest accuracy. The developed algorithm identified Still's murmur with 90.0% sensitivity and 98.3% specificity for the default decision threshold. The area under the receiver operating characteristic curve was 0.943. Still's murmur can be identified with high accuracy with the algorithm we developed. Using this approach, the algorithm could help to reduce the rate of unnecessary pediatric cardiologist referrals and use of echocardiography for a common benign finding.
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影响因子：
7.7
作者：
Choi, Samjin;Jiang, Zhongwei
通讯作者：
Jiang, Zhongwei
影响因子：
5.1
作者：
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通讯作者：
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DOI：
10.1002/chp.1340220304
发表时间：
2002-01-01
期刊：
The Journal of continuing education in the health professions
影响因子：
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通讯作者：
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作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
McCrindle, BW