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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
Future Directions: Artificial Intelligence and Digital Tools in Bladder Cancer Care
Tommy Jiang1, Calvin C Zhao1, Joseph C Liao1
1Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA.
Abstract:
This comprehensive review examines using artificial intelligence (AI) across the diagnostic, therapeutic, and prognostic landscape of bladder cancer. It highlights AI's capacity to enhance tumor detection, histopathologic interpretation, surgical precision, and personalized treatment planning through machine learning and computer vision. Applications such as AI-assisted cystoscopy, cytology, transurethral resection of bladder tumor optimization, and prognostic modeling demonstrate significant potential to reduce variability and improve clinical decision-making. While early evidence is promising, widespread implementation requires rigorous validation, multicenter collaboration, and regulatory standardization. Ultimately, AI represents a paradigm shift toward data-driven, precision-based bladder cancer management which can potentially transform patient outcomes globally.
