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A deep database of medical abbreviations and acronyms for natural language processing

, Raymond H. Grossman, Elliot G. Mitchell, Chunhua Weng, Karthik Natarajan, George Hripcsak, David K. Vawdrey
Published: 2 June 2021
Scientific Data , Volume 8, pp 1-9; doi:10.1038/s41597-021-00929-4

Abstract: The recognition, disambiguation, and expansion of medical abbreviations and acronyms is of upmost importance to prevent medically-dangerous misinterpretation in natural language processing. To support recognition, disambiguation, and expansion, we present the Medical Abbreviation and Acronym Meta-Inventory, a deep database of medical abbreviations. A systematic harmonization of eight source inventories across multiple healthcare specialties and settings identified 104,057 abbreviations with 170,426 corresponding senses. Automated cross-mapping of synonymous records using state-of-the-art machine learning reduced redundancy, which simplifies future application. Additional features include semi-automated quality control to remove errors. The Meta-Inventory demonstrated high completeness or coverage of abbreviations and senses in new clinical text, a substantial improvement over the next largest repository (6–14% increase in abbreviation coverage; 28–52% increase in sense coverage). To our knowledge, the Meta-Inventory is the most complete compilation of medical abbreviations and acronyms in American English to-date. The multiple sources and high coverage support application in varied specialties and settings. This allows for cross-institutional natural language processing, which previous inventories did not support. The Meta-Inventory is available at https://bit.ly/github-clinical-abbreviations.
Keywords: Meta Inventory / medical abbreviations and acronyms / coverage / language processing / natural language

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