Disambiguating Clinical Abbreviations by One-to-All Classification: Algorithm Development and Validation Study

• Published in: JMIR medical informatics Vol. 12; p. e56955
• Main Authors: Sung, Sheng-Feng, Hu, Ya-Han, Chen, Chong-Yan
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 01.10.2024
• Subjects: Abbreviations; Abbreviations as Topic; AI Language Models in Health Care; Algorithms; Amputation; Batch processing; Case Study; Clinical decision making; Datasets; Electronic Health Records; Hospitals; Humans; Machine Learning; Medical records; Natural Language Processing; Original Paper; Subject heading schemes; Validation studies; Word sense disambiguation; text mining; word sense disambiguation; electronic medical records; abbreviation expansion; natural language processing

Electronic medical records store extensive patient data and serve as a comprehensive repository, including textual medical records like surgical and imaging reports. Their utility in clinical decision support systems is substantial, but the widespread use of ambiguous and unstandardized abbreviation...