Proceedings of the 4th Clinical Natural Language Processing Workshop 2022
DOI: 10.18653/v1/2022.clinicalnlp-1.8
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Learning to Ask Like a Physician

Abstract: Existing question answering (QA) datasets derived from electronic health records (EHR) are artificially generated and consequently fail to capture realistic physician information needs. We present Discharge Summary Clinical Questions (DiSCQ), a newly curated question dataset composed of 2,000+ questions paired with the snippets of text (triggers) that prompted each question. The questions are generated by medical experts from 100+ MIMIC-III discharge summaries. We analyze this dataset to characterize the types… Show more

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Cited by 7 publications
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