Use of machine learning to predict early biochemical recurrence after robot‐assisted prostatectomy

OBJECTIVES: To train and compare machine-learning algorithms with traditional regression analysis for the prediction of early biochemical recurrence after robot-assisted prostatectomy. PATIENTS AND METHODS: A prospectively collected dataset of 338 patients who underwent robot-assisted prostatectomy for localized prostate cancer was examined. We used three supervised machine-learning algorithms and 19 different training variables (demographic, …