Machine learning-based survival prediction in colorectal cancer combining clinical and biological features (2025)
- Authors:
- Autor USP: SETUBAL, JOÃO CARLOS - IQ
- Unidade: IQ
- DOI: 10.18632/oncotarget.28783
- Subjects: NEOPLASIAS COLORRETAIS; RNA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Oncotarget
- ISSN: 1949-2553
- Volume/Número/Paginação/Ano: v. 16, p. 834-847, 2025
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
VIEIRA, Lucas M et al. Machine learning-based survival prediction in colorectal cancer combining clinical and biological features. Oncotarget, v. 16, p. 834-847, 2025Tradução . . Disponível em: https://dx.doi.org/10.18632/oncotarget.28783. Acesso em: 10 fev. 2026. -
APA
Vieira, L. M., Jorge, N. A. N., Sousa, J. B., Setubal, J. C., Stadler, P. F., & Walter, M. E. M. T. (2025). Machine learning-based survival prediction in colorectal cancer combining clinical and biological features. Oncotarget, 16, 834-847. doi:10.18632/oncotarget.28783 -
NLM
Vieira LM, Jorge NAN, Sousa JB, Setubal JC, Stadler PF, Walter MEMT. Machine learning-based survival prediction in colorectal cancer combining clinical and biological features [Internet]. Oncotarget. 2025 ; 16 834-847.[citado 2026 fev. 10 ] Available from: https://dx.doi.org/10.18632/oncotarget.28783 -
Vancouver
Vieira LM, Jorge NAN, Sousa JB, Setubal JC, Stadler PF, Walter MEMT. Machine learning-based survival prediction in colorectal cancer combining clinical and biological features [Internet]. Oncotarget. 2025 ; 16 834-847.[citado 2026 fev. 10 ] Available from: https://dx.doi.org/10.18632/oncotarget.28783 - Complete genome sequence of the potato pathogen Ralstonia solanacearum UY031
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Informações sobre o DOI: 10.18632/oncotarget.28783 (Fonte: oaDOI API)
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