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. 2021 Feb 16;143(13):1287–1298. doi: 10.1161/CIRCULATIONAHA.120.047829

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© 2021 The Authors.

Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial-NoDerivs License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited, the use is noncommercial, and no modifications or adaptations are made.

This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

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Figure 3. — ROC curves, incidence-free KM survival curves, and HRs in subpopulations for the 3 models evaluated on the holdout set. The 3 models are XGBoost model with age and sex only (blue); DNN model with ECG traces only (DNN-ECG; red); and DNN model with ECG traces, age, and sex (DNN-ECG-AS; black) for all ECGs in the holdout set. A, ROC curves with operating points marked for the 3 models. B, Incidence-free KM curves for the high- and low-risk groups for the operating point shown in A for a follow-up of 30 years. Note that curves corresponding to the low-risk group for all 3 models overlap. C, The plot of HR with 95% CIs for the 3 models in subpopulations defined by age groups, sex, and normal or abnormal ECG label. Note that there is no HR for age <50 years for the first model as there was no subject classified as high-risk for new-onset atrial fibrillation by the model for that subpopulation. DNN indicates deep neural network; HR, hazard ratio; KM, Kaplan-Meier; and ROC, receiver operating characteristic.