Semi-Supervised Learning for Multi-Label Cardiovascular Diseases Prediction: A Multi-Dataset Study

Electrocardiography (ECG) is a non-invasive tool for predicting cardiovascular diseases (CVDs). Current ECG-based diagnosis systems show promising performance owing to the rapid development of deep learning techniques. However, the label scarcity problem, the co-occurrence of multiple CVDs and the p...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2024-05, Vol.46 (5), p.3305-3320
Hauptverfasser:	Zhou, Rushuang, Lu, Lei, Liu, Zijun, Xiang, Ting, Liang, Zhen, Clifton, David A., Dong, Yining, Zhang, Yuan-Ting
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Cardiovascular diseases Cardiovascular Diseases - diagnostic imaging Correlation Data augmentation Data models Datasets Deep learning Diagnostic systems Distillation electrocardiograph Electrocardiography Humans Labels Machine learning Modules multi-label learning Predictions Predictive models Semi-supervised learning Semisupervised learning Supervised Machine Learning Training
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