Multi-domain Feature Fusion Neural Network for Electrocardiogram Classification
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-30111-7_24
Reference20 articles.
1. Gordon, P., Kerton, M.: Cardiac arrhythmias in the critically ill. Anaesth. Intensive Care Med. 22(5), 301–321 (2021)
2. Barcos, J.C., Humphreys, J.D., Santacruz, I.A.T., et al.: Enhancing electrocardiographic analysis by combining a high-resolution 12-lead ECG with novel software tools. J. Electrocardiol. 70, 70–74 (2022)
3. De Lannoy, G., Francois, D., Delbeke, J., et al.: Weighted conditional random fields for supervised interpatient heartbeat classification. IEEE Trans. Biomed. Eng. 59(1), 241–247 (2012)
4. Daamouche, A., Hamami, L., Alajlan, N., et al.: A wavelet optimization approach for ECG signal classification. Biomed. Signal Process. Control 7(4), 342–349 (2012)
5. Sharma, P., Dinkar, S.K., Gupta, D.V.: A novel hybrid deep learning method with cuckoo search algorithm for classification of arrhythmia disease using ECG signals. Neural Comput. Appl. 33(19), 13123–13143 (2021)
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