Matches in SemOpenAlex for { <https://semopenalex.org/work/W2081955728> ?p ?o ?g. }
- W2081955728 endingPage "35" @default.
- W2081955728 startingPage "35" @default.
- W2081955728 abstract "Objectives Although acronyms and abbreviations in clinical text are used widely on a daily basis, relatively little research has focused upon word sense disambiguation (WSD) of acronyms and abbreviations in the healthcare domain. Since clinical notes have distinctive characteristics, it is unclear whether techniques effective for acronym and abbreviation WSD from biomedical literature are sufficient. Methods The authors discuss feature selection for automated techniques and challenges with WSD of acronyms and abbreviations in the clinical domain. Results There are significant challenges associated with the informal nature of clinical text, such as typographical errors and incomplete sentences; difficulty with insufficient clinical resources, such as clinical sense inventories; and obstacles with privacy and security for conducting research with clinical text. Although we anticipated that using sophisticated techniques, such as biomedical terminologies, semantic types, part-of-speech, and language modeling, would be needed for feature selection with automated machine learning approaches, we found instead that simple techniques, such as bag-of-words, were quite effective in many cases. Factors, such as majority sense prevalence and the degree of separateness between sense meanings, were also important considerations. Conclusions The first lesson is that a comprehensive understanding of the unique characteristics of clinical text is important for automatic acronym and abbreviation WSD. The second lesson learned is that investigators may find that using simple approaches is an effective starting point for these tasks. Finally, similar to other WSD tasks, an understanding of baseline majority sense rates and separateness between senses is important. Further studies and practical solutions are needed to better address these issues. Keywords: Abbreviations as Topic, Medical Records, Natural Language Processing, Artificial Intelligence, Automated Pattern Recognition" @default.
- W2081955728 created "2016-06-24" @default.
- W2081955728 creator A5004688014 @default.
- W2081955728 creator A5025398350 @default.
- W2081955728 creator A5083901654 @default.
- W2081955728 date "2015-01-01" @default.
- W2081955728 modified "2023-10-16" @default.
- W2081955728 title "Challenges and Practical Approaches with Word Sense Disambiguation of Acronyms and Abbreviations in the Clinical Domain" @default.
- W2081955728 cites W1512170015 @default.
- W2081955728 cites W15359877 @default.
- W2081955728 cites W1548184736 @default.
- W2081955728 cites W1550258693 @default.
- W2081955728 cites W1573048037 @default.
- W2081955728 cites W1577541759 @default.
- W2081955728 cites W1656666520 @default.
- W2081955728 cites W1756650108 @default.
- W2081955728 cites W1894023216 @default.
- W2081955728 cites W192539577 @default.
- W2081955728 cites W1984293430 @default.
- W2081955728 cites W1993068388 @default.
- W2081955728 cites W2019911971 @default.
- W2081955728 cites W2033200726 @default.
- W2081955728 cites W2114388055 @default.
- W2081955728 cites W2114420708 @default.
- W2081955728 cites W2115871101 @default.
- W2081955728 cites W2121758668 @default.
- W2081955728 cites W2133990480 @default.
- W2081955728 cites W2162108374 @default.
- W2081955728 cites W1485174548 @default.
- W2081955728 cites W1509072985 @default.
- W2081955728 doi "https://doi.org/10.4258/hir.2015.21.1.35" @default.
- W2081955728 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4330198" @default.
- W2081955728 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25705556" @default.
- W2081955728 hasPublicationYear "2015" @default.
- W2081955728 type Work @default.
- W2081955728 sameAs 2081955728 @default.
- W2081955728 citedByCount "32" @default.
- W2081955728 countsByYear W20819557282016 @default.
- W2081955728 countsByYear W20819557282018 @default.
- W2081955728 countsByYear W20819557282019 @default.
- W2081955728 countsByYear W20819557282020 @default.
- W2081955728 countsByYear W20819557282021 @default.
- W2081955728 countsByYear W20819557282022 @default.
- W2081955728 countsByYear W20819557282023 @default.
- W2081955728 crossrefType "journal-article" @default.
- W2081955728 hasAuthorship W2081955728A5004688014 @default.
- W2081955728 hasAuthorship W2081955728A5025398350 @default.
- W2081955728 hasAuthorship W2081955728A5083901654 @default.
- W2081955728 hasBestOaLocation W20819557281 @default.
- W2081955728 hasConcept C134306372 @default.
- W2081955728 hasConcept C138885662 @default.
- W2081955728 hasConcept C154945302 @default.
- W2081955728 hasConcept C204321447 @default.
- W2081955728 hasConcept C23123220 @default.
- W2081955728 hasConcept C2524010 @default.
- W2081955728 hasConcept C2776401178 @default.
- W2081955728 hasConcept C28719098 @default.
- W2081955728 hasConcept C33923547 @default.
- W2081955728 hasConcept C36503486 @default.
- W2081955728 hasConcept C41008148 @default.
- W2081955728 hasConcept C41895202 @default.
- W2081955728 hasConcept C482391 @default.
- W2081955728 hasConcept C81917197 @default.
- W2081955728 hasConceptScore W2081955728C134306372 @default.
- W2081955728 hasConceptScore W2081955728C138885662 @default.
- W2081955728 hasConceptScore W2081955728C154945302 @default.
- W2081955728 hasConceptScore W2081955728C204321447 @default.
- W2081955728 hasConceptScore W2081955728C23123220 @default.
- W2081955728 hasConceptScore W2081955728C2524010 @default.
- W2081955728 hasConceptScore W2081955728C2776401178 @default.
- W2081955728 hasConceptScore W2081955728C28719098 @default.
- W2081955728 hasConceptScore W2081955728C33923547 @default.
- W2081955728 hasConceptScore W2081955728C36503486 @default.
- W2081955728 hasConceptScore W2081955728C41008148 @default.
- W2081955728 hasConceptScore W2081955728C41895202 @default.
- W2081955728 hasConceptScore W2081955728C482391 @default.
- W2081955728 hasConceptScore W2081955728C81917197 @default.
- W2081955728 hasIssue "1" @default.
- W2081955728 hasLocation W20819557281 @default.
- W2081955728 hasLocation W20819557282 @default.
- W2081955728 hasLocation W20819557283 @default.
- W2081955728 hasLocation W20819557284 @default.
- W2081955728 hasLocation W20819557285 @default.
- W2081955728 hasOpenAccess W2081955728 @default.
- W2081955728 hasPrimaryLocation W20819557281 @default.
- W2081955728 hasRelatedWork W2054565523 @default.
- W2081955728 hasRelatedWork W2119214692 @default.
- W2081955728 hasRelatedWork W2357241418 @default.
- W2081955728 hasRelatedWork W2366644548 @default.
- W2081955728 hasRelatedWork W2368651715 @default.
- W2081955728 hasRelatedWork W2376314740 @default.
- W2081955728 hasRelatedWork W2384888906 @default.
- W2081955728 hasRelatedWork W2611614995 @default.
- W2081955728 hasRelatedWork W3107474891 @default.
- W2081955728 hasRelatedWork W4221154112 @default.
- W2081955728 hasVolume "21" @default.
- W2081955728 isParatext "false" @default.
- W2081955728 isRetracted "false" @default.