Optimized dual threshold entity resolution for electronic health record databases--training set size and active learning.

Joffe, Erel; Byrne, Michael J; Reeder, Phillip; Herskovic, Jorge R; Johnson, Craig W; McCoy, Allison B; Bernstam, Elmer V

Joffe, Erel; Byrne, Michael J; Reeder, Phillip; Herskovic, Jorge R; Johnson, Craig W; McCoy, Allison B; Bernstam, Elmer V.

Afiliação

Joffe E; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.
Byrne MJ; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.
Reeder P; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.
Herskovic JR; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX. ; Department of Bioinformatics and Computational Biology, MD Anderson Cancer Center, Houston, TX.
Johnson CW; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.
McCoy AB; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX. ; UT Houston - Memorial Hermann Center for Healthcare Quality & Safety, Houston, TX.
Bernstam EV; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX. ; Division of General Internal Medicine, Department of Internal Medicine, Medical School, The University of Texas Health Science Center at Houston, Houston, TX.

AMIA Annu Symp Proc ; 2013: 721-30, 2013.

Article em En | MEDLINE | ID: mdl-24551372

Assuntos

Algoritmos; Inteligência Artificial; Registros Eletrônicos de Saúde; Lógica Fuzzy

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Inteligência Artificial / Registros Eletrônicos de Saúde Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2013 Tipo de documento: Article

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