MERIT applies information theory to ECG representation learning via masked modeling and ECG-text contrastive alignment, reporting F1 gains over 3% on PTB-XL All and 5% on SubClass plus zero-shot and text generation improvements.
arXiv preprint arXiv:2411.00755 (2024)
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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HeartBeatAI reports 98% Macro F1 under intra-source testing on four ECG datasets but shows significant degradation on rare anomalies under leave-one-domain-out evaluation.
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HeartBeatAI: An Interpretable and Robust Deep Learning Framework for Multi-Label ECG Arrhythmia Detection
HeartBeatAI reports 98% Macro F1 under intra-source testing on four ECG datasets but shows significant degradation on rare anomalies under leave-one-domain-out evaluation.