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CADENCE uses sparse autoencoders to decompose ECG foundation model representations into interpretable physiological concepts, significantly improving alignment with clinical phenotypes and waveform morphology.
MedicalBench is a new benchmark for evaluating large language models on medical concept extraction from electronic health records, focusing on implicit reasoning and evidence grounding. It includes 823 expert-annotated examples and shows that current models perform modestly, highlighting the difficulty of extracting implicitly stated medical concepts.