Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks

Andrew Y. Ng; Awni Y. Hannun; Codie Bourn; Masoumeh Haghpanahi; Pranav Rajpurkar

arxiv: 1707.01836 · v1 · pith:DZ334E7Wnew · submitted 2017-07-06 · 💻 cs.CV

Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks

Pranav Rajpurkar , Awni Y. Hannun , Masoumeh Haghpanahi , Codie Bourn , Andrew Y. Ng This is my paper

classification 💻 cs.CV

keywords cardiologistsperformanceconvolutionaldatasetneuralsequencealgorithmannotate

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We develop an algorithm which exceeds the performance of board certified cardiologists in detecting a wide range of heart arrhythmias from electrocardiograms recorded with a single-lead wearable monitor. We build a dataset with more than 500 times the number of unique patients than previously studied corpora. On this dataset, we train a 34-layer convolutional neural network which maps a sequence of ECG samples to a sequence of rhythm classes. Committees of board-certified cardiologists annotate a gold standard test set on which we compare the performance of our model to that of 6 other individual cardiologists. We exceed the average cardiologist performance in both recall (sensitivity) and precision (positive predictive value).

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