ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012
Combining corpus-derived sense profiles with estimated frequency information to disambiguate clinical abbreviations.
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 15 papers.
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Who cites it
15 citing papers in PubMed.
- Clinical Note Structural Knowledge Improves Word Sense Disambiguation.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Sequence Labeling for Disambiguating Medical Abbreviations.Journal of healthcare informatics research · 2023Article
- Deciphering clinical abbreviations with a privacy protecting machine learning system.Nature communications · 2022Article
- Biomedical word sense disambiguation with bidirectional long short-term memory and attention-based neural networks.BMC bioinformatics · 2019Article
- Language model-based automatic prefix abbreviation expansion method for biomedical big data analysis.Future generations computer systems : FGCS · 2019Article
- Interactive medical word sense disambiguation through informed learning.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Knowledge-Based Biomedical Word Sense Disambiguation with Neural Concept EmbeddingsProceedings. IEEE International Symposium on Bioinformatics and Bioengineering · 2017Article
- A long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD).Journal of the American Medical Informatics Association : JAMIA · 2017Article
- Distinction between medical and non-medical usages of short forms in clinical narratives.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- Towards Comprehensive Clinical Abbreviation Disambiguation Using Machine-Labeled Training Data.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Detection of sentence boundaries and abbreviations in clinical narratives.BMC medical informatics and decision making · 2015Article
- A Preliminary Study of Clinical Abbreviation Disambiguation in Real Time.Applied clinical informatics · 2015Article
- Validating a strategy for psychosocial phenotyping using a large corpus of clinical text.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- A comparative study of current Clinical Natural Language Processing systems on handling abbreviations in discharge summaries.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2012Article
- Word sense disambiguation in the clinical domain: a comparison of knowledge-rich and knowledge-poor unsupervised methods.Journal of the American Medical Informatics Association : JAMIAArticle
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Authors and funding
3 authors.
Funding
Abstract
Abbreviations are widely used in clinical notes and are often ambiguous. Word sense disambiguation (WSD) for clinical abbreviations therefore is a critical task for many clinical natural language processing (NLP) systems. Supervised machine learning based WSD methods are known for their high performance. However, it is time consuming and costly to construct annotated samples for supervised WSD approaches and sense frequency information is often ignored by these methods. In this study, we proposed a profile-based method that used dictated discharge summaries as an external source to automatically build sense profiles and applied them to disambiguate abbreviations in hospital admission notes via the vector space model. Our evaluation using a test set containing 2,386 annotated instances from 13 ambiguous abbreviations in admission notes showed that the profile-based method performed better than two baseline methods and achieved a best average precision of 0.792. Furthermore, we developed a strategy to combine sense frequency information estimated from a clustering analysis with the profile-based method. Our results showed that the combined approach largely improved the performance and achieved a highest precision of 0.875 on the same test set, indicating that integrating sense frequency information with local context is effective for clinical abbreviation disambiguation.
Indexed as
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23304376PMC3540457What 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.