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. Author manuscript; available in PMC: 2021 Feb 10.
Published in final edited form as: Comput Biol Med. 2020 Oct 15;127:104057. doi: 10.1016/j.compbiomed.2020.104057

Table 3.

Performance of the proposed model for the AF classification task on the PhysioNet Computing in Cardiology Challenge 2017 dataset (AFDB17).

Method Database Best Performance (%)
Sensitivity Specificity Accuracy AUC
HAN-ECG3 AFDB17 86.02 98.62 96.98 98.46
HAN-ECG2 AFDB17 86.15 98.50 96.90 98.41
HAN-ECG1 AFDB17 84.30 98.48 96.64 98.44
RNN AFDB17 80.52 97.40 95.18 97.18