ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012
A comparative study of current Clinical Natural Language Processing systems on handling abbreviations in discharge summaries.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
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- Deciphering clinical abbreviations with a privacy protecting machine learning system.Nature communications · 2022Article
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- Drug knowledge discovery via multi-task learning and pre-trained models.BMC medical informatics and decision making · 2021Article
- A deep database of medical abbreviations and acronyms for natural language processing.Scientific data · 2021Article
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- Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports.Journal of biomedical informatics · 2020Article
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- Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.Journal of biomedical semantics · 2019Article
- Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining Approach.JMIR medical informatics · 2019Article
- Automatic extraction and assessment of lifestyle exposures for Alzheimer's disease using natural language processing.International journal of medical informatics · 2019Article
- Making sense of abbreviations in nursing notes: A case study on mortality prediction.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Evaluating the Impact of Dictionary Updates on Automatic Annotations Based on Clinical NLP Systems.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- A method for harmonization of clinical abbreviation and acronym sense inventories.Journal of biomedical informatics · 2018Article
- Expanding a radiology lexicon using contextual patterns in radiology reports.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- The Data Gap in the EHR for Clinical Research Eligibility Screening.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
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6 authors.
Funding
Abstract
Clinical Natural Language Processing (NLP) systems extract clinical information from narrative clinical texts in many settings. Previous research mentions the challenges of handling abbreviations in clinical texts, but provides little insight into how well current NLP systems correctly recognize and interpret abbreviations. In this paper, we compared performance of three existing clinical NLP systems in handling abbreviations: MetaMap, MedLEE, and cTAKES. The evaluation used an expert-annotated gold standard set of clinical documents (derived from from 32 de-identified patient discharge summaries) containing 1,112 abbreviations. The existing NLP systems achieved suboptimal performance in abbreviation identification, with F-scores ranging from 0.165 to 0.601. MedLEE achieved the best F-score of 0.601 for all abbreviations and 0.705 for clinically relevant abbreviations. This study suggested that accurate identification of clinical abbreviations is a challenging task and that more advanced abbreviation recognition modules might improve existing clinical NLP systems.
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23304375PMC3540461What OpenQuestion holds
Registered trials
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