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Explainable Electrocardiogram Interpretation using Deep Learning-based Semantic Segmentation
DOI:10.1093/ehjdh/ztag122.png)
Abstract
En 中文
Accurate electrocardiogram (ECG) waveform delineation, rhythm classification, and median beat generation are interdependent steps whose joint modeling improves consistency for downstream computerized diagnostic tasks. This study aimed to develop a lead-agnostic segmentation model that performs these tasks by segmenting individual leads and aggregating predictions in postprocessing.
Journal
E
IF:
4.4
Papers:
830
Citations:
949

