ArticleScientific data2021
A deep database of medical abbreviations and acronyms for natural language processing.
Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Article
- Auto-expansion software prompting reduces abbreviation use in electronic hospital discharge letters: an observational pre- and post-intervention study.BMC medical informatics and decision making · 2025Observational
- RAMIE: retrieval-augmented multi-task information extraction with large language models on dietary supplements.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Analyzing the Creation and Use of Abbreviations in Cardiology and Cardiac Imaging Society Guidelines.JACC. Advances · 2025Article
- Multimodal BEHRT: transformers for multimodal electronic health records to predict breast cancer prognosis.Frontiers in oncology · 2025Article
- Disambiguating Clinical Abbreviations by One-to-All Classification: Algorithm Development and Validation Study.JMIR medical informatics · 2024Article
- Processing of Short-Form Content in Clinical Narratives: Systematic Scoping Review.Journal of medical Internet research · 2024Article
- Artificial intelligence to unlock real-world evidence in clinical oncology: A primer on recent advances.Cancer medicine · 2024Review
- Remote Diagnosis on Upper Respiratory Tract Infections Based on a Neural Network with Few Symptom Words-A Feasibility Study.Diagnostics (Basel, Switzerland) · 2024Article
- A Novel Sentence Transformer-based Natural Language Processing Approach for Schema Mapping of Electronic Health Records to the OMOP Common Data Model.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Word sense disambiguation of acronyms in clinical narratives.Frontiers in digital health · 2024Article
- Towards a practical use of text mining approaches in electrodiagnostic data.Scientific reports · 2023Article
- Article
- Predicting relations between SOAP note sections: The value of incorporating a clinical information model.Journal of biomedical informatics · 2023Article
- The potential of a data centred approach & knowledge graph data representation in chemical safety and drug design.Computational and structural biotechnology journal · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
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 .
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.