Classification of Patient’s Heartbeat Obtained by ECG Using Active Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-7346-8_49
Reference29 articles.
1. Kiranyaz S, Ince T, Gabbouj M (2015) Real-time patient-specific ECG classification by 1-D convolutional neural networks. IEEE Trans Biomed Eng 63(3):664–675
2. Niu X, Han H, Shan S, Chen X (2018) SynRhythm: learning a deep heart rate estimator from general to specific. In: Proceedings of international conference on pattern recognition, vol 2018, no i, Aug 2018, pp 3580–3585. https://doi.org/10.1109/ICPR.2018.8546321
3. Weimann K, Conrad TOF (2021) Transfer learning for ECG classification. Sci Rep 11(1):1–12
4. Gupta V, Saxena NK, Kanungo A, Gupta A, Kumar P et al (2022) A review of different ECG classification/detection techniques for improved medical applications. Int J Syst Assur Eng Manag 1–15
5. Syed Z, Guttag J, Stultz C (2007) Clustering and symbolic analysis of cardiovascular signals: discovery and visualization of medically relevant patterns in long-term data using limited prior knowledge. EURASIP J Adv Signal Process 2007. https://doi.org/10.1155/2007/67938
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