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Prostate cancer (PCa) is a cancer with a broad spectrum of biological behavior and it is a heterogeneous nature. In order to prevent overdiagnosis and overtreatment, and to detect clinically significant PCa, standardized scoring and grading systems are used in imaging and pathological examinations. However, reproducibility and agreement between readers in these diagnostic stages, which require experience, are low. Promising results have been achieved by integrating artificial intelligence (AI)-based applications into the diagnosis and management of PCa. In radiological and pathological imaging, computer-aided diagnostic tools have increased clinical efficiency and achieved diagnostic accuracy comparable to that of experienced healthcare professionals. This review provides an overview of AI applications used in radiological imaging, prostate biopsy, and histopathological examination in the diagnosis of PCa.
Alçın et al. (Wed,) studied this question.