Postoperatory risk classification of prostate cancer patients using support vector machines

This paper proposes a classification scheme of prostate cancer patients based on support vector machines (SVM) classifiers that allow including the diagnosed prostate cancer patients into risk classes, before performing radical prostatectomy, according to their medical parameters. Our objective is to assess the use of SVM in order to predict the individual result of radical prostatectomy performed on prostate cancer patients. In medicine, the balance now leans over towards practical experience, as there are more and more information and knowledge on which physicians base their decisions. The treatment options may be different from patient to patient. The surgical decision about prostate cancer is often a complex matter; thus the proposed schema is a very useful tool that allows the physician to benefit from information regarding the outcome of previous cases.