Mostafa Ahmed Arafa1,2, Karim Hamda Farhat1,*, Nesma Lotfy3, Farrukh Kamel Khan1, Alaa Mokhtar4, Abdulaziz Mohammed Althunayan1, Waleed Al-Taweel4, Sultan Saud Al-Khateeb4, Sami Azhari1,5, Danny Munther Rabah1,4
Canadian Journal of Urology, Vol.32, No.3, pp. 173-180, 2025, DOI:10.32604/cju.2025.066016
- 27 June 2025
Abstract Background: Transrectal (TR) and transperineal (TP) biopsies are commonly used methods for diagnosing prostate cancer. However, their comparative effectiveness in conjunction with machine learning (ML) techniques remains underexplored. This study aimed to evaluate the predictive accuracy of ML algorithms in detecting prostate cancer using data derived from TR and TP biopsies. Methods: The clinical records of patients who underwent prostate biopsy at King Saud University Medical City and King Faisal Specialist Hospital and Research Centerin Riyadh, Saudi Arabia, between 2018 and 2025 were analyzed. Data were used to train and test ML models, including eXtreme… More >