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| Automated atrial fibrillation recognition in 12-lead electrocardiographic records: a signal to image and transfer learning approach: A case-control accuracy study |
| Elena Caires Silveira |
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Precis Future Med. 2021;5(4):184-189. Published online December 28, 2021 DOI: https://doi.org/10.23838/pfm.2021.00058 |
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Automated atrial fibrillation recognition in 12-lead electrocardiographic records: a signal to image and transfer learning approach: A case-control accuracy study Precision and Future Medicine. 2021;5(4):184-189  Automated Signal Quality Assessment of Single-Lead ECG Recordings for Early Detection of Silent Atrial Fibrillation Sensors. 2023;23(12):5618 Filtering strategies of electrocardiographic imaging signals for stratification of atrial fibrillation patients Biomedical Signal Processing and Control. 2023;81:104438 Deep transfer learning for automated liver cancer gene recognition using spectrogram images of digitized DNA sequences Biomedical Signal Processing and Control. 2022;72:103317 Enhancing Atrial Fibrillation detection accuracy: A wavelet transform filtered single lead ECG signal analysis with artificial neural networks and novel feature extraction Machine Learning with Applications. 2023;12:100472 Stacking segment-based CNN with SVM for recognition of atrial fibrillation from single-lead ECG recordings Biomedical Signal Processing and Control. 2021;68:102672 An objective approach to identifying individual atrial fibrillation triggers: A simulation study Biomedical Signal Processing and Control. 2024;87:105369 Automated human emotion recognition using hybrid approach based on sensitivity analysis on residual time-frequency plane with online learning algorithm Biomedical Signal Processing and Control. 2023;84:104913 Atrial fibrillation detection with and without atrial activity analysis using lead-I mobile ECG technology Biomedical Signal Processing and Control. 2021;66:102462 Identification of spatiotemporal dispersion electrograms in atrial fibrillation ablation using machine learning: A comparative study Biomedical Signal Processing and Control. 2022;72:103269 |
