LLMs match or beat supervised BERT models on detecting whether a discharge note contains an actionable clinical task but trail on classifying the exact type of action, pointing to the need for datasets that explain why each span was labeled actionable.
MedDecXtract: A clinician-support system for extracting, visualizing, and annotating medical decisions in clinical narratives
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Systematic Evaluation of Large Language Models for Post-Discharge Clinical Action Extraction
LLMs match or beat supervised BERT models on detecting whether a discharge note contains an actionable clinical task but trail on classifying the exact type of action, pointing to the need for datasets that explain why each span was labeled actionable.