Machuca-Aguado, J.; Conde-MartÃn, A.F.; Alvarez-Muñoz, A.; RodrÃguez-Zarco, E.; Polo-Velasco, A.; Rueda-Ramos, A.; Rendón-GarcÃa, R.; RÃos-Martin, J.J.; Idoate, M.A.
Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas. Int. J. Mol. Sci. 2023, 24, 16060.
https://doi.org/10.3390/ijms242216060
AMA Style
Machuca-Aguado J, Conde-MartÃn AF, Alvarez-Muñoz A, RodrÃguez-Zarco E, Polo-Velasco A, Rueda-Ramos A, Rendón-GarcÃa R, RÃos-Martin JJ, Idoate MA.
Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas. International Journal of Molecular Sciences. 2023; 24(22):16060.
https://doi.org/10.3390/ijms242216060
Chicago/Turabian Style
Machuca-Aguado, Jesús, Antonio Félix Conde-MartÃn, Alejandro Alvarez-Muñoz, Enrique RodrÃguez-Zarco, Alfredo Polo-Velasco, Antonio Rueda-Ramos, Rosa Rendón-GarcÃa, Juan José RÃos-Martin, and Miguel A. Idoate.
2023. "Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas" International Journal of Molecular Sciences 24, no. 22: 16060.
https://doi.org/10.3390/ijms242216060
APA Style
Machuca-Aguado, J., Conde-MartÃn, A. F., Alvarez-Muñoz, A., RodrÃguez-Zarco, E., Polo-Velasco, A., Rueda-Ramos, A., Rendón-GarcÃa, R., RÃos-Martin, J. J., & Idoate, M. A.
(2023). Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas. International Journal of Molecular Sciences, 24(22), 16060.
https://doi.org/10.3390/ijms242216060