Clinical pathways and hierarchical clustering for tuberculosis treatment outcome prediction (2023)
Yamaguti, Verena Hokino 
; Freitas, Alberto; Apunike, Anderson Chidi; Rijo, Rui Pedro Charters Lopes; Alves, Domingos ; Netto, Antonio Ruffino
Source: Procedia Computer Science. Unidades: FMRP, BIOENGENHARIA
Subjects: TUBERCULOSE, SAÚDE PÚBLICA, APRENDIZADO COMPUTACIONAL, REGISTROS MÉDICOS
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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: 10 nov. 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.2023.01.425NLM
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 nov. 10 ] Available from: https://doi.org/10.1016/j.procs.2023.01.425Vancouver
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 nov. 10 ] Available from: https://doi.org/10.1016/j.procs.2023.01.425
