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Natural language processing utilization in healthcare

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dc.citedby8
dc.contributor.authorHudaa S.en_US
dc.contributor.authorSetiyadi D.B.P.en_US
dc.contributor.authorLaxmi Lydia E.en_US
dc.contributor.authorShankar K.en_US
dc.contributor.authorNguyen P.T.en_US
dc.contributor.authorHashim W.en_US
dc.contributor.authorMaseleno A.en_US
dc.contributor.authorid57211402461en_US
dc.contributor.authorid57211407608en_US
dc.contributor.authorid57196059278en_US
dc.contributor.authorid56884031900en_US
dc.contributor.authorid57216386109en_US
dc.contributor.authorid11440260100en_US
dc.contributor.authorid55354910900en_US
dc.date.accessioned2023-05-29T07:24:05Z
dc.date.available2023-05-29T07:24:05Z
dc.date.issued2019
dc.description.abstractThe significance of consolidating Natural Language Processing (NLP) techniques in clinical informatics research has been progressively perceived over the previous years, and has prompted transformative advances. Ordinarily, clinical NLP frameworks are created and assessed on word, sentence, or record level explanations that model explicit traits and highlights, for example, archive content (e.g., persistent status, or report type), record segment types (e.g., current meds, past restorative history, or release synopsis), named substances and ideas (e.g., analyses, side effects, or medicines) or semantic qualities (e.g., nullification, seriousness, or fleetingness). While some NLP undertakings consider expectations at the individual or gathering client level, these assignments still establish a minority. Here we give an expansive synopsis and layout of the difficult issues engaged with characterizing suitable natural and outward assessment strategies for NLP look into that will be utilized for clinical results research, and the other way around. A specific spotlight is set on psychological wellness investigate, a zone still generally understudied by the clinical NLP look into network, however where NLP techniques are of prominent importance. Ongoing advances in clinical NLP strategy improvement have been huge, yet we propose more accentuation should be put on thorough assessment for the field to progress further. To empower this, we give noteworthy recommendations, including an insignificant convention that could be utilized when announcing clinical NLP strategy improvement and its assessment. � BEIESP.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.35940/ijeat.F1305.0886S219
dc.identifier.epage1120
dc.identifier.issue6 Special Issue 2
dc.identifier.scopus2-s2.0-85073805006
dc.identifier.spage1117
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85073805006&doi=10.35940%2fijeat.F1305.0886S219&partnerID=40&md5=3962c23b9dd129c4e43715c1f240e1e1
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24511
dc.identifier.volume8
dc.publisherBlue Eyes Intelligence Engineering and Sciences Publicationen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleInternational Journal of Engineering and Advanced Technology
dc.titleNatural language processing utilization in healthcareen_US
dc.typeArticleen_US
dspace.entity.typePublication
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