Minority class–aware multiclass arrhythmia detection using conditional GAN augmentation

Abstract The detection of cardiac arrhythmias from electrocardiogram (ECG) signals is essential for preventing sudden cardiac deaths. However, model performance on minority classes, such as supraventricular (S) and fusion (F) beats, which make up less than 3% of samples, is severely hampered by seve...

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Hlavní autoři:	Abhishek Tiwari, Jaydeep Kishore, Rohit Singh
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2026-05-01
Edice:	Scientific Reports
Témata:	Detection of cardiac arrhythmias Deep learning Class imbalance Conditional Wasserstein GAN Data augmentation
On-line přístup:	https://doi.org/10.1038/s41598-026-51237-z
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