A split-and-match weak supervision pipeline trains BERT and BiLSTM models to extract and link medical entities from chief complaints without human annotation, achieving 67.5 F1 on a clinician-labeled test set.
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Weakly Supervised Medical Entity Extraction and Linking for Chief Complaints
A split-and-match weak supervision pipeline trains BERT and BiLSTM models to extract and link medical entities from chief complaints without human annotation, achieving 67.5 F1 on a clinician-labeled test set.