Abstract
Abstract: Prostate cancer is the second biggest cause of mortality in men, according to statistics. It's said to be a slow-growing malignancy that doesn't exhibit symptoms until it’s advanced. Over the last few years, numerous studies on AI algorithms processing various medical imaging such as CT, MRI, and Ultrasound have been conducted. Using AI to manage prostate cancer would have a significant influence on healthcare. With almost 1.3 million new cases identified each year around the world, cancer experts would have a better grasp of the disease and be able to generate more accurate cancer detection forecasts. We give a review of the usage of CNN applied to several automatic processing tasks of prostate cancer detection and diagnosis, to provide an overview of the progress in this field, based on the increased interest of CNN in recent years. We've noticed that the use of CNN has skyrocketed, with outstanding results obtained either with fresh models or employing pre-trained networks for transfer learning. According to the results of the survey, deep learning-based research outperforms traditional patient prognosis techniques in terms of accuracy. Keywords: Convolutional Neural Network, Deep Learning, Prostate Cancer Detection, Artificial Intelligence, Survey.
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