di Noia, C.; Grist, J.T.; Riemer, F.; Lyasheva, M.; Fabozzi, M.; Castelli, M.; Lodi, R.; Tonon, C.; Rundo, L.; Zaccagna, F.
Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI. Diagnostics 2022, 12, 2125.
https://doi.org/10.3390/diagnostics12092125
AMA Style
di Noia C, Grist JT, Riemer F, Lyasheva M, Fabozzi M, Castelli M, Lodi R, Tonon C, Rundo L, Zaccagna F.
Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI. Diagnostics. 2022; 12(9):2125.
https://doi.org/10.3390/diagnostics12092125
Chicago/Turabian Style
di Noia, Christian, James T. Grist, Frank Riemer, Maria Lyasheva, Miriana Fabozzi, Mauro Castelli, Raffaele Lodi, Caterina Tonon, Leonardo Rundo, and Fulvio Zaccagna.
2022. "Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI" Diagnostics 12, no. 9: 2125.
https://doi.org/10.3390/diagnostics12092125
APA Style
di Noia, C., Grist, J. T., Riemer, F., Lyasheva, M., Fabozzi, M., Castelli, M., Lodi, R., Tonon, C., Rundo, L., & Zaccagna, F.
(2022). Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI. Diagnostics, 12(9), 2125.
https://doi.org/10.3390/diagnostics12092125
