AI-DRIVEN APPROACH FOR EARLY PROSTATE CANCER DETECTION AND DIAGNOSIS

Abstract

Prostate cancer develops in the prostate glands in men, located below the bladder. Prostate cancer is becoming the prominent cause of death among men. It grows slowly and may not show any symptoms in the early stage. Many procedures are being used to treat Prostate cancer, but they are not getting better results yet at the early stage. Deep learning models, such as YOLO, have a significant impact on medical imaging due to their high accuracy and real-time object detection capabilities. The study supports the integration of advanced AI models (YOLOv11) into clinical workflows for prostate cancer diagnosis at an early stage. The model is very efficient, achieving a 92.56% validation accuracy, average 98.61% Precision, average 93.91% Recall, average 96.19% F-1 score, and Area under the Curve (AUC) 96%-to-98%.