Janbain, A., Spohn, S. K. B., Grosu, A.-L., & Shelan, M. [ca. 2024]. A machine learning approach for predicting biochemical outcome after PSMA-PET–guided salvage radiotherapy in recurrent prostate cancer after radical prostatectomy: retrospective study [Cd]. Freiburg: Universität. https://doi.org/10.2196/60323

JANBAIN, Ali, SPOHN, Simon Konrad Benedict, GROSU, Anca-Ligia und SHELAN, Mohamed, 2024. A machine learning approach for predicting biochemical outcome after PSMA-PET–guided salvage radiotherapy in recurrent prostate cancer after radical prostatectomy: retrospective study. Freiburg: Universität.

Janbain, A., S. K. B. Spohn, A.-L. Grosu, und M. Shelan. A machine learning approach for predicting biochemical outcome after PSMA-PET–guided salvage radiotherapy in recurrent prostate cancer after radical prostatectomy: retrospective study. cd, Universität, 2024, https://doi.org/10.2196/60323.

Janbain, Ali/Spohn, Simon Konrad Benedict/Grosu, Anca-Ligia/Shelan, Mohamed: A machine learning approach for predicting biochemical outcome after PSMA-PET–guided salvage radiotherapy in recurrent prostate cancer after radical prostatectomy: retrospective study, Freiburg 2024.

Janbain, A., Spohn, S.K.B., Grosu, A.-L. und Shelan, M. (2024), A machine learning approach for predicting biochemical outcome after PSMA-PET–guided salvage radiotherapy in recurrent prostate cancer after radical prostatectomy: retrospective study, Bd. , Universität, Freiburg, verfügbar unter:https://doi.org/10.2196/60323.