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ECG-Lense Benchmarking ML Amp DL Models On PTB-XL Dataset by nimratkr256 is a document available to read on EtoBox.

What is ECG-Lense Benchmarking ML Amp DL Models On PTB-XL Dataset about?

This study benchmarks machine learning (ML) and deep learning (DL) models for the classification of ECG signals using the PTB-XL dataset, which includes recordings from normal patients and those with various cardiac conditions. The research compares traditional ML algorithms with advanced DL models, revealing that the Complex CNN (ECG-Lense) achieved the highest classification accuracy of 80% and a ROC-AUC of 90%. The findings aim to enhance automated ECG interpretation, ultimately improving patient care an

Author

nimratkr256

Language

EN