Cita APA (7a ed.)
Nakajo, M., Jinguji, M., Tani, A., Kikuno, H., Hirahara, D., Togami, S., . . . Yoshiura, T. (2021). Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [18F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer. Molecular Imaging & Biology, 23(5), 756-766.
Cita Chicago Style (17a ed.)
Nakajo, Masatoyo, Megumi Jinguji, Atsushi Tani, Hidehiko Kikuno, Daisuke Hirahara, Shinichi Togami, Hiroaki Kobayashi, y Takashi Yoshiura. "Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [18F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer." Molecular Imaging & Biology 23, no. 5 (2021): 756-766.
Cita MLA (9a ed.)
Nakajo, Masatoyo, et al. "Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [18F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer." Molecular Imaging & Biology, vol. 23, no. 5, 2021, pp. 756-766.
Precaución: Estas citas no son 100% exactas.