Schenone, D.; Dominietto, A.; Campi, C.; Frassoni, F.; Cea, M.; Aquino, S.; Angelucci, E.; Rossi, F.; Torri, L.; Bignotti, B.;
et al. Radiomics and Artificial Intelligence for Outcome Prediction in Multiple Myeloma Patients Undergoing Autologous Transplantation: A Feasibility Study with CT Data. Diagnostics 2021, 11, 1759.
https://doi.org/10.3390/diagnostics11101759
AMA Style
Schenone D, Dominietto A, Campi C, Frassoni F, Cea M, Aquino S, Angelucci E, Rossi F, Torri L, Bignotti B,
et al. Radiomics and Artificial Intelligence for Outcome Prediction in Multiple Myeloma Patients Undergoing Autologous Transplantation: A Feasibility Study with CT Data. Diagnostics. 2021; 11(10):1759.
https://doi.org/10.3390/diagnostics11101759
Chicago/Turabian Style
Schenone, Daniela, Alida Dominietto, Cristina Campi, Francesco Frassoni, Michele Cea, Sara Aquino, Emanuele Angelucci, Federica Rossi, Lorenzo Torri, Bianca Bignotti,
and et al. 2021. "Radiomics and Artificial Intelligence for Outcome Prediction in Multiple Myeloma Patients Undergoing Autologous Transplantation: A Feasibility Study with CT Data" Diagnostics 11, no. 10: 1759.
https://doi.org/10.3390/diagnostics11101759
APA Style
Schenone, D., Dominietto, A., Campi, C., Frassoni, F., Cea, M., Aquino, S., Angelucci, E., Rossi, F., Torri, L., Bignotti, B., Tagliafico, A. S., & Piana, M.
(2021). Radiomics and Artificial Intelligence for Outcome Prediction in Multiple Myeloma Patients Undergoing Autologous Transplantation: A Feasibility Study with CT Data. Diagnostics, 11(10), 1759.
https://doi.org/10.3390/diagnostics11101759
