Artificial intelligence: a new era in prostate cancer diagnosis and treatment

Prostate cancer (PCa) represents one of the most prevalent cancers among men, with substantial challenges in timely and accurate diagnosis and subsequent treatment. Traditional diagnosis and treatment methods for PCa, such as prostate-specific antigen (PSA) biomarker detection, digital rectal examination, imaging (CT/MRI) analysis, and biopsy histopathological examination, suffer from limitations such as a lack of specificity, generation of false positives or negatives, and difficulty in handling large data, leading to overdiagnosis and overtreatment. The integration of artificial intelligence (AI) in PCa diagnosis and treatment is revolutionizing traditional approaches by offering advanced tools for early detection, personalized treatment planning, and patient management. AI technologies, especially machine learning and deep learning, improve diagnostic accuracy and treatment planning. The AI algorithms analyze imaging data, like MRI and ultrasound, to identify cancerous lesions effectively with great precision. In addition, AI algorithms enhance risk assessment and prognosis by combining clinical, genomic, and imaging data. This leads to more tailored treatment strategies, enabling informed decisions about active surveillance, surgery, or new therapies, thereby improving quality of life while reducing unnecessary diagnoses and treatments. This review examines current AI applications in PCa care, focusing on their transformative impact on diagnosis and treatment planning while recognizing potential challenges. It also outlines expected improvements in diagnosis through AI-integrated systems and decision support tools for healthcare teams. The findings highlight AI's potential to enhance clinical outcomes, operational efficiency, and patient-centred care in managing PCa.