Supervised classifiers of prostate cancer from magnetic resonance images in T2 sequences

The prostate in size is like a walnut and is located in front of the rectum and under the bladder. It is located only in men. Prostate cancer also known as prostate cancer, is the most common malignant tumor in men and the second most common cause of cancer-related death in men, because of this you see the importance of deepening in this type of cancer, in order to achieve significant progress, in terms of its diagnosis. This research is focused on the development of a Machine Learning Machine Learning (ML) System, using Magnetic Resonance Imaging (MRI) of human beings and analyzing the structures involved, by means of the extraction of geometric characteristics, taking into account the evaluation categories PI-RADS, the best measure of performance in terms of accuracy according to the models evaluated was through logistic regression with 0.831, likewise, this study is aimed at the support of professionals in oncology; focused on the diagnosis of prostate cancer. This system aims to be a timely aid, in cancer patients, hospital centers, oncologists who are experts in cancer and for all those interested in improving the diagnosis of prostate cancer.