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Classification Method of ECG Signals Based on RANet.

Aoxiang ZhangXinwu YangTong LiMengfei DouHongxiao Yang
Published in: Cardiovascular engineering and technology (2024)
Experiments and verifications are conducted using the PhysioNet/CinC Challenge 2017 dataset. The average F1 value is 0.817, which is 0.064 higher than that for the ResNet model. Compared with the mainstream methods, the performance is excellent.
Keyphrases
  • machine learning
  • deep learning
  • heart rate variability
  • heart rate
  • blood pressure