Coada, C.A.; Santoro, M.; Zybin, V.; Di Stanislao, M.; Paolani, G.; Modolon, C.; Di Costanzo, S.; Genovesi, L.; Tesei, M.; De Leo, A.;
et al. A Radiomic-Based Machine Learning Model Predicts Endometrial Cancer Recurrence Using Preoperative CT Radiomic Features: A Pilot Study. Cancers 2023, 15, 4534.
https://doi.org/10.3390/cancers15184534
AMA Style
Coada CA, Santoro M, Zybin V, Di Stanislao M, Paolani G, Modolon C, Di Costanzo S, Genovesi L, Tesei M, De Leo A,
et al. A Radiomic-Based Machine Learning Model Predicts Endometrial Cancer Recurrence Using Preoperative CT Radiomic Features: A Pilot Study. Cancers. 2023; 15(18):4534.
https://doi.org/10.3390/cancers15184534
Chicago/Turabian Style
Coada, Camelia Alexandra, Miriam Santoro, Vladislav Zybin, Marco Di Stanislao, Giulia Paolani, Cecilia Modolon, Stella Di Costanzo, Lucia Genovesi, Marco Tesei, Antonio De Leo,
and et al. 2023. "A Radiomic-Based Machine Learning Model Predicts Endometrial Cancer Recurrence Using Preoperative CT Radiomic Features: A Pilot Study" Cancers 15, no. 18: 4534.
https://doi.org/10.3390/cancers15184534
APA Style
Coada, C. A., Santoro, M., Zybin, V., Di Stanislao, M., Paolani, G., Modolon, C., Di Costanzo, S., Genovesi, L., Tesei, M., De Leo, A., Ravegnini, G., De Biase, D., Morganti, A. G., Lovato, L., De Iaco, P., Strigari, L., & Perrone, A. M.
(2023). A Radiomic-Based Machine Learning Model Predicts Endometrial Cancer Recurrence Using Preoperative CT Radiomic Features: A Pilot Study. Cancers, 15(18), 4534.
https://doi.org/10.3390/cancers15184534
