PCV50 Automatic Classification of Electronic Health Records for a Value-Based Program through Machine Learning

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dc.contributor.authorZanotto, Bruna
dc.contributor.authorEtdges, Ana Paula
dc.contributor.authorDal Bosco, Avner
dc.contributor.authorCortes, Eduardo
dc.contributor.authorVieira, Renata
dc.contributor.authorRuschel, R
dc.contributor.authorMartins, S
dc.contributor.authorSouza, A
dc.contributor.authorValiense, C
dc.contributor.authorViegas, F
dc.contributor.authorCanutto, S
dc.contributor.authorGonçalves, M
dc.contributor.authorPolanczyk, C
dc.date.accessioned2022-04-26T15:01:56Z
dc.date.available2022-04-26T15:01:56Z
dc.date.issued2021
dc.description.abstractThis study presents a comparative assessment of supervised machine learning (ML) methods to capture outcomes and patients' characteristics from electronic health records (EHR). We explored automatic classification of free-text data from EHRs to support a value-based program.por
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dc.identifier.authoremailrenatav@uevora.pt
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dc.identifier.citationB. Zanotto, A.P. Etges, A. Dal Bosco, E.G. Cortes, R. Ruschel, S.O. Martins, A.C. Souza, C. Valiense, F. Viegas, S. Canuto, W. Luiz, R. Vieira, M. Gonçalves, C.A. Polanczyk, PCV50 Automatic Classification of Electronic Health Records for a Value-Based Program through Machine Learning, Value in Health,Volume 24, Supplement 1, 2021, Page S76, ISSN 1098-3015, https://doi.org/10.1016/j.jval.2021.04.389. (https://www.sciencedirect.com/science/article/pii/S1098301521006069)por
dc.identifier.doi10.1016/j.jval.2021.04.389por
dc.identifier.scientificarea283por
dc.identifier.urihttp://hdl.handle.net/10174/31826
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherElsevierpor
dc.rightsrestrictedAccesspor
dc.titlePCV50 Automatic Classification of Electronic Health Records for a Value-Based Program through Machine Learningpor
dc.typearticlepor

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