Rabilloud, N.; Allaume, P.; Acosta, O.; De Crevoisier, R.; Bourgade, R.; Loussouarn, D.; Rioux-Leclercq, N.; Khene, Z.-e.; Mathieu, R.; Bensalah, K.;
et al. Deep Learning Methodologies Applied to Digital Pathology in Prostate Cancer: A Systematic Review. Diagnostics 2023, 13, 2676.
https://doi.org/10.3390/diagnostics13162676
AMA Style
Rabilloud N, Allaume P, Acosta O, De Crevoisier R, Bourgade R, Loussouarn D, Rioux-Leclercq N, Khene Z-e, Mathieu R, Bensalah K,
et al. Deep Learning Methodologies Applied to Digital Pathology in Prostate Cancer: A Systematic Review. Diagnostics. 2023; 13(16):2676.
https://doi.org/10.3390/diagnostics13162676
Chicago/Turabian Style
Rabilloud, Noémie, Pierre Allaume, Oscar Acosta, Renaud De Crevoisier, Raphael Bourgade, Delphine Loussouarn, Nathalie Rioux-Leclercq, Zine-eddine Khene, Romain Mathieu, Karim Bensalah,
and et al. 2023. "Deep Learning Methodologies Applied to Digital Pathology in Prostate Cancer: A Systematic Review" Diagnostics 13, no. 16: 2676.
https://doi.org/10.3390/diagnostics13162676
APA Style
Rabilloud, N., Allaume, P., Acosta, O., De Crevoisier, R., Bourgade, R., Loussouarn, D., Rioux-Leclercq, N., Khene, Z.-e., Mathieu, R., Bensalah, K., Pecot, T., & Kammerer-Jacquet, S.-F.
(2023). Deep Learning Methodologies Applied to Digital Pathology in Prostate Cancer: A Systematic Review. Diagnostics, 13(16), 2676.
https://doi.org/10.3390/diagnostics13162676