Automatic Classification of Evidence Based Medicine Using Transformers

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dc.contributor.authorBolücü, Necva
dc.contributor.authorHepsa?, Pınar Uskaner
dc.date.accessioned2025-01-06T17:29:44Z
dc.date.available2025-01-06T17:29:44Z
dc.date.issued2022
dc.description20th Annual Workshop of the Australasian Language Technology Association, ALTA 2022 -- 14 December 2022 through 16 December 2022 -- Adelaide -- 310649
dc.description.abstractThe goal of the shared task is multi-label classification for biomedical records in English used for Evidence-Based Medicine. In this paper, we describe the model based on the Transformer submitted by our team turkNLP for the shared task. Our model achieved a Micro ROC score of ? 0.93 on the shared task and ranked 5th in the leaderboard. © 2020, Australasian Language Technology Association. All rights reserved.
dc.identifier.issn1834-7037
dc.identifier.scopus2-s2.0-85190660030
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1327
dc.identifier.volume20
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherAustralasian Language Technology Association
dc.relation.ispartofProceedings of the Australasian Language Technology Workshop
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.titleAutomatic Classification of Evidence Based Medicine Using Transformers
dc.typeConference Object

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