Sabino, Alan Utsuni 
; Ribeiro, Adriana Vaz Safatle ; Lima, Suzylaine da Silva ; Marques, Carlos Frederico Sparapan ; Maluf Filho, Fauze ; Ramos, Alexandre Ferreira
Source: Critical Reviews in Oncogenesis. Unidades: FM, EACH
Assunto: NEOPLASIAS
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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: 27 abr. 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 abr. 27 ] 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 abr. 27 ] Available from: http://dx.doi.org/10.1615/CritRevOncog.2023050075
