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Deep learning has advanced automated electrocardiogram (ECG) diagnosis, but the field's most accurate models, foundation models pretrained on millions of recordings, are not decision-pathway auditable: a clinician cannot trace a diagnosis to a physiological pathway or intervene on one. We propose TRACE, a Tractable Rou...
LiteMedCoT-VL is introduced, a pipeline that transfers chain-of-thought reasoning from a 235B teacher model to 2B student models through LoRA-based fine-tuning on explanation-enriched training data, and indicates that a 2B model with reasoning distillation can match or exceed models with twice the parameters.
BEAT-Net is presented, a supervised biomimetic framework that integrates QRS-centered biological tokenization with a hierarchical architecture mirroring the cardiologist's workflow, demonstrating that explicit physiological structure provides a more efficient and interpretable alternative to massive pre-training for cl...
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