MACHINE LEARNING MODELS FOR PREDICTION OF PROSTATE CANCER
IZOGIE, L. E., AKAZUE, M. I.2 AND IHAMA, E.I.
ABSTRACT
Prostate cancer comprises of the enlargement or increase in the magnitude of the prostate biopsies and a shortage of urological pathologists, and this constrains the diagnosis of prostate cancers. There are several predictive model to predict and manage prostate cancer, developed by different authors which involves the interpretation of data using aggregate mode to assist in determination and making accurate decision. Different means sure as PSA rate, MRI guided biopsies, genomics biomarkers, and Gleason scaling system are utilized for predicting the risk, to stratify, and observe patients during individual follow-ups. However, identification tracking and successive risk categorization oftentimes alter..