Table 11 Benchmarking with other DL for AF detection
From: AFibNet: an implementation of atrial fibrillation detection with convolutional neural network
Authors | Method | Total subject | Acc. (%) | Sens. (%) | Spec. | ROC-AUC Score (%) |
|---|---|---|---|---|---|---|
Faust et al. [4] | RNNs-LSTM | 102 | 98.51 | – | – | – |
Hong et al. [51] | CNNs-RNNs | ± 20,000 | – | – | – | 98.57 |
Zhang et al. [52] | CNNs | 177,941 | 91.88 | 94.23 | – | – |
Yildirim et al. [53] | DNNs | 3605 | 97.91 | 96.52 | 98.31 | – |
Proposed model | 1D-CNNs | 8416 | 100 | 100 | 100 | – |
|  |  | 11,842 | 98.94 | 98.97 | 98.97 | – |
| Â | Â | 26,349 | 96.36 | 93.65 | 96.92 | - |