DeepArrhythmia introduces a segment-contextualized multimodal framework for beat-level ECG arrhythmia classification that uses tool-grounded evidence extraction and selective acquisition routed by segment-level confidence.
Evaluating large language models on time series feature understanding: A comprehensive taxonomy and benchmark
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DeepArrhythmia: Segment-Contextualized ECG Arrhythmia Classification via Selective Evidence Acquisition
DeepArrhythmia introduces a segment-contextualized multimodal framework for beat-level ECG arrhythmia classification that uses tool-grounded evidence extraction and selective acquisition routed by segment-level confidence.