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Historical visit attendance as predictor of treatment interruption in South African HIV patients: Extension of a validated machine learning model.
Esra, Rachel T; Carstens, Jacques; Estill, Janne; Stoch, Ricky; Le Roux, Sue; Mabuto, Tonderai; Eisenstein, Michael; Keiser, Olivia; Maskew, Mhari; Fox, Matthew P; De Voux, Lucien; Sharpey-Schafer, Kieran.
Afiliação
  • Esra RT; Institute of Global Health, University of Geneva, Geneva, Switzerland.
  • Carstens J; Imperial College of London, London, United Kingdom.
  • Estill J; Palindrome Data, Cape Town, South Africa.
  • Stoch R; Institute of Global Health, University of Geneva, Geneva, Switzerland.
  • Le Roux S; Studio Fundi Ltd, London, United Kingdom.
  • Mabuto T; The Aurum Institute, Johannesburg, South Africa.
  • Eisenstein M; The Aurum Institute, Johannesburg, South Africa.
  • Keiser O; The Aurum Institute, Johannesburg, South Africa.
  • Maskew M; Institute of Global Health, University of Geneva, Geneva, Switzerland.
  • Fox MP; Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  • De Voux L; Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  • Sharpey-Schafer K; Departments of Epidemiology and Global Health, Boston University School of Public Health, Boston, Massachusetts, United States of America.
PLOS Glob Public Health ; 3(7): e0002105, 2023.
Article em En | MEDLINE | ID: mdl-37467217
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 1_ASSA2030 Problema de saúde: 1_sistemas_informacao_saude Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLOS Glob Public Health Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Suíça
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 1_ASSA2030 Problema de saúde: 1_sistemas_informacao_saude Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLOS Glob Public Health Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Suíça