Published August 31, 2022 | Version v1
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Atrial Fibrillation Risk Prediction from Row ECG - Pre-trained Deep Neural Network Models

  • 1. Department of Information Technology, Uppsala University, Sweden
  • 2. Faculty of Biomedical Engineering, Technion—Israel Institute of Technology, Israel.
  • 3. Department of Internal Medicine, Faculdade de Medicina, Universidade Federal de Minas Gerais—UFMG, Brazil


This is a pre-trained deep neural network (DNN) model for risk prediction of atrial fibrillation (AF) from row ECG samples.

From ECG data, the model can predict whether a patient is with AF condition, whether a patient is without the condition and without the risk or whether a patient is at risk of developing AF in the near future (within 7 years). The output from the DNN model can then be applied on a survival model for further risk analysis.

The companion code can be found in:


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