Sequence Labeling for Disambiguating Medical Abbreviations

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dc.contributor.authorCevik, Mucahit
dc.contributor.authorJafari, Sanaz Mohammad
dc.contributor.authorMyers, Mitchell
dc.contributor.authorYildirim, Savas
dc.date.accessioned2024-07-18T20:42:28Z
dc.date.available2024-07-18T20:42:28Z
dc.date.issued2023
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description.abstractAbbreviations are unavoidable yet critical parts of the medical text. Using abbreviations, especially in clinical patient notes, can save time and space, protect sensitive information, and help avoid repetitions. However, most abbreviations might have multiple senses, and the lack of a standardized mapping system makes disambiguating abbreviations a difficult and time-consuming task. The main objective of this study is to examine the feasibility of sequence labeling methods for medical abbreviation disambiguation. Specifically, we explore the capability of sequence labeling methods to deal with multiple unique abbreviations in a single text. We use two public datasets to compare and contrast the performance of several transformer models pre-trained on different scientific and medical corpora. Our proposed sequence labeling approach outperforms the more commonly used text classification models for the abbreviation disambiguation task. In particular, the SciBERT model shows a strong performance for both sequence labeling and text classification tasks over the two considered datasets. Furthermore, we find that abbreviation disambiguation performance for the text classification models becomes comparable to that of sequence labeling only when postprocessing is applied to their predictions, which involves filtering possible labels for an abbreviation based on the training data.en_US
dc.identifier.doi10.1007/s41666-023-00146-1
dc.identifier.endpage526en_US
dc.identifier.issn2509-4971
dc.identifier.issn2509-498X
dc.identifier.issue4en_US
dc.identifier.pmid37927372en_US
dc.identifier.scopus2-s2.0-85170847000en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage501en_US
dc.identifier.urihttps://doi.org/10.1007/s41666-023-00146-1
dc.identifier.urihttps://hdl.handle.net/11411/7277
dc.identifier.volume7en_US
dc.identifier.wosWOS:001065959600001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSpringernatureen_US
dc.relation.ispartofJournal of Healthcare Informatics Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAbbreviation Disambiguationen_US
dc.subjectMedical Texten_US
dc.subjectSequence Labelingen_US
dc.subjectTransformers Modelsen_US
dc.subjectRecognitionen_US
dc.titleSequence Labeling for Disambiguating Medical Abbreviationsen_US
dc.typeArticleen_US

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