Evaluation reveals 68.9% of extracted medical terms can be improved in teaching clinical research protocols, suggesting better dictionary support is needed.
This study aims to support the expressions adjustment in teaching clinical research protocols through computer assistance by evaluating the accuracy of extracting medical and clinical trial-related terms using existing natural language processing (NLP) tools and the Unified Medical Language System (UMLS) developed by the U.S. National Library of Medicine as a dictionary. Of the 671 unique terms and 939 total terms that did not match the manual validation, 462 unique terms (68.9%) and 518 total terms (55.2%) were deemed improvable through rule-based methods.Addressing these statistical terms could be achieved by adding domain-specific terminology to the dictionary, although variations in expression, such as "detection rate" versus "statistical power" or "1-β," pose additional challenges.
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Nishimoto et al. (2025) studied this question.
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