AI RESEARCH
ExECG: An Explainable AI Framework for ECG models
arXiv CS.AI
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ArXi:2605.19258v1 Announce Type: cross Deep learning has enabled ECG diagnostic models with strong performance in tasks such as arrhythmia classification and abnormality detection. However, accuracy alone is insufficient for clinical deployment because it does not explain why a specific output was produced, limiting justification, error analysis, and trust. Although ECG XAI has been extensively investigated and steadily improved, practical pipelines and reporting conventions vary across studies, hindering reuse and reproducibility.