AI RESEARCH
ECG Classification on PTB-XL: A Data-Centric Approach with Simplified CNN-VAE
arXiv CS.LG
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ArXi:2603.07558v1 Announce Type: new Automated electrocardiogram (ECG) classification is essential for early detection of cardiovascular diseases. While recent approaches have increasingly relied on deep neural networks with complex architectures, we nstrate that careful data preprocessing, class balancing, and a simplified convolutional neural network combined with a variational autoencoder (CNN-VAE) architecture can achieve competitive performance with significantly reduced model complexity.