Deep Learning-Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography.

ABSTRACT: Background Severe, symptomatic aortic stenosis (AS) is associated with poor prognoses. However, early detection of AS is difficult because of the long asymptomatic period experienced by many patients, during which screening tools are ineffective. The aim of this study was to develop and validate a deep learning-based algorithm, combining a multilayer perceptron and convolutional neural network, for detecting significant AS using ECGs. Methods and Results This retrospective cohort study included adult patients who had undergone both ECG and echocardiography. A deep learning-based algorithm was developed using 39 371 ECGs. Internal validation of the algorithm was performed with 6453 ECGs from one hospital, and external validation was performed with 10 865 ECGs from another hospital. The end

SUBMITTER: Kwon JM 

PROVIDER: S-EPMC7428650 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature