Position: Evaluation of ECG Representations Must Be Fixed

Researchers argue that current benchmarking practices in 12-lead ECG representation learning need to be revised to include broader clinical targets beyond arrhythmia for more reliable progress. They highlight that a randomly initialized encoder performs comparably to state-of-the-art models on many tasks, suggesting the use of such encoders as baseline models. For content creators in medical research, this implies a shift towards more comprehensive and clinically relevant evaluation metrics when developing ECG analysis tools.

Read the full article at arXiv cs.LG (ML)

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