AmpliNetECG12, a 280k-parameter CNN with a softmax-based activation, reports an F1 score of 80.7% and ROC-AUC of 97% on the CPSC2018 12-lead ECG arrhythmia benchmark using 50 Hz data.
This performance was achieved with a model comprising only 280,000 trainable parameters and while analyzing ECG data sampled at a frequency of just 50Hz
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AmpliNetECG12: A lightweight SoftMax-based relativistic amplitude amplification architecture for 12 lead ECG classification
AmpliNetECG12, a 280k-parameter CNN with a softmax-based activation, reports an F1 score of 80.7% and ROC-AUC of 97% on the CPSC2018 12-lead ECG arrhythmia benchmark using 50 Hz data.