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 [cd]. Freiburg: Universität. doi:10.2196/60323.
Chicago Manual of Style 17th edition (full note)Janbain, Ali, Simon Konrad Benedict Spohn, Anca-Ligia Grosu, und Mohamed 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. Freiburg: Universität, [2024?], Freiburg: Universität, [2024?]. https://doi.org/10.2196/60323.
American Psychological Association 7th editionJanbain, 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]. Universität. https://doi.org/10.2196/60323
Modern Language Association 9th editionJanbain, 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.
ISO-690 (author-date, Deutsch)JANBAIN, Ali, Simon Konrad Benedict SPOHN, Anca-Ligia GROSU und Mohamed SHELAN, 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