Clinical pathways and hierarchical clustering for tuberculosis treatment outcome prediction (2023)
- Autores:
- Autores USP: ALVES, DOMINGOS - FMRP ; RIJO, RUI PEDRO CHARTERS LOPES - BIOENGENHARIA ; NETTO, ANTONIO RUFFINO - FMRP ; YAMAGUTI, VERENA HOKINO - FMRP
- Unidades: FMRP; BIOENGENHARIA
- DOI: 10.1016/j.procs.2023.01.425
- Assuntos: TUBERCULOSE; SAÚDE PÚBLICA; APRENDIZADO COMPUTACIONAL; REGISTROS MÉDICOS
- Palavras-chave do autor: Tuberculosis; Clinical pathways; Process mining; Public health; Clustering; Machine Learning
- Agências de fomento:
- Idioma: Inglês
- Imprenta:
- Fonte:
- Título do periódico: Procedia Computer Science
- ISSN: 1877-0509
- Volume/Número/Paginação/Ano: v. 219, p. 1373-1379, 2023
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
-
ABNT
YAMAGUTI, Verena Hokino et al. Clinical pathways and hierarchical clustering for tuberculosis treatment outcome prediction. Procedia Computer Science, v. 219, p. 1373-1379, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.procs.2023.01.425. Acesso em: 25 jul. 2024. -
APA
Yamaguti, V. H., Freitas, A., Apunike, A. C., Rijo, R. P. C. L., Alves, D., & Netto, A. R. (2023). Clinical pathways and hierarchical clustering for tuberculosis treatment outcome prediction. Procedia Computer Science, 219, 1373-1379. doi:10.1016/j.procs.2023.01.425 -
NLM
Yamaguti VH, Freitas A, Apunike AC, Rijo RPCL, Alves D, Netto AR. Clinical pathways and hierarchical clustering for tuberculosis treatment outcome prediction [Internet]. Procedia Computer Science. 2023 ; 219 1373-1379.[citado 2024 jul. 25 ] Available from: https://doi.org/10.1016/j.procs.2023.01.425 -
Vancouver
Yamaguti VH, Freitas A, Apunike AC, Rijo RPCL, Alves D, Netto AR. Clinical pathways and hierarchical clustering for tuberculosis treatment outcome prediction [Internet]. Procedia Computer Science. 2023 ; 219 1373-1379.[citado 2024 jul. 25 ] Available from: https://doi.org/10.1016/j.procs.2023.01.425 - Development of CART model for prediction of tuberculosis treatment loss to follow up in the state of São Paulo, Brazil: a case–control study
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Informações sobre o DOI: 10.1016/j.procs.2023.01.425 (Fonte: oaDOI API)
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