Yahya Ghazwani1,2,3, Mohammad Alghafees1,2,3,*, Mishari Alshasha1,2,3, Fahad Brayan1,2,3, Abdulrahman Alsayyari1,2,3, Ali Alyami1,2,3
Canadian Journal of Urology, Vol.33, No.2, pp. 291-308, 2026, DOI:10.32604/cju.2026.077411
- 20 April 2026
Abstract Objectives: The emergence of artificial intelligence (AI) and predictive modeling offers prospects for clinical, anatomical, and imaging factor combination, like radiomics, to help with stone-free status (SFS) estimation and peroperative decision-making. The goal of this study was, therefore, to define the present performance range, determine sources of heterogeneity, and determine methodological practices permitting reliable implementation by varied circumstances. Methods: We searched six bibliographic databases through 19 September 2025. Studies deriving or validating AI/predictive models for SFS after ureteroscopy were eligible. Independent dual screening, duplicate data extraction, and risk-of-bias consideration using QUADAS-AI were conducted. Results: Five retrospective… More >