Source: Critical Reviews in Oncogenesis. Unidades: FM, EACH
Assunto: NEOPLASIAS
ABNT
SABINO, Alan Utsuni et al. Machine learning-based prediction of responsiveness to neoadjuvant chemoradiotheapy in locally advanced rectal cancer patients from endomicroscopy. Critical Reviews in Oncogenesis, v. 29, n. 2, p. 53-63, 2024Tradução . . Disponível em: http://dx.doi.org/10.1615/CritRevOncog.2023050075. Acesso em: 04 out. 2024.APA
Sabino, A. U., Ribeiro, A. V. S., Lima, S. da S., Marques, C. F. S., Maluf Filho, F., & Ramos, A. F. (2024). Machine learning-based prediction of responsiveness to neoadjuvant chemoradiotheapy in locally advanced rectal cancer patients from endomicroscopy. Critical Reviews in Oncogenesis, 29( 2), 53-63. doi:10.1615/CritRevOncog.2023050075NLM
Sabino AU, Ribeiro AVS, Lima S da S, Marques CFS, Maluf Filho F, Ramos AF. Machine learning-based prediction of responsiveness to neoadjuvant chemoradiotheapy in locally advanced rectal cancer patients from endomicroscopy [Internet]. Critical Reviews in Oncogenesis. 2024 ; 29( 2): 53-63.[citado 2024 out. 04 ] Available from: http://dx.doi.org/10.1615/CritRevOncog.2023050075Vancouver
Sabino AU, Ribeiro AVS, Lima S da S, Marques CFS, Maluf Filho F, Ramos AF. Machine learning-based prediction of responsiveness to neoadjuvant chemoradiotheapy in locally advanced rectal cancer patients from endomicroscopy [Internet]. Critical Reviews in Oncogenesis. 2024 ; 29( 2): 53-63.[citado 2024 out. 04 ] Available from: http://dx.doi.org/10.1615/CritRevOncog.2023050075