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Bayesian latent class models for identifying canine visceral leishmaniosis using diagnostic tests in the absence of a gold standard.
Ozanne, Marie V; Brown, Grant D; Scorza, Breanna M; Mahachi, Kurayi; Toepp, Angela J; Petersen, Christine A.
Afiliação
  • Ozanne MV; Department of Mathematics & Statistics, Mount Holyoke College, South Hadley, Massachusetts, United States of America.
  • Brown GD; Department of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa, United States of America.
  • Scorza BM; Department of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, United States of America.
  • Mahachi K; Department of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, United States of America.
  • Toepp AJ; Enterprise Analytics, Sentara Healthcare, Virginia Beach, Virginia, United States of America.
  • Petersen CA; Department of Internal Medicine, Eastern Virginia Medical School, Norfolk, Virginia, United States of America.
PLoS Negl Trop Dis ; 16(3): e0010236, 2022 03.
Article em En | MEDLINE | ID: mdl-35286301
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Leishmania infantum / Doenças do Cão / Leishmaniose Visceral Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Leishmania infantum / Doenças do Cão / Leishmaniose Visceral Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article