@article{article_1577208, title={The Use of Artificial Intelligence in Pediatric Kidney Stone Disease}, journal={Samsun Medical Journal}, volume={3}, pages={1–2}, year={2025}, author={Önal, Hülya Gözde}, keywords={pediatric kidney stone, Al}, abstract={This letter highlights the role of AI in enhancing diagnosis and treatment in pediatric kidney stone disease. AI, especially through machine learning algorithms such as convolutional neural networks, performs highly accurately in detecting kidney stones through medical imaging-a modality that can further improve diagnostic precision and speed. AI also enables personalized treatment by analyzing a wide range of genetic, metabolic, and clinical information to tailor therapies and predict recurrence risk. With AI-enabled devices, real-time monitoring of patients can be ensured, thus helping patients maintain hydration, physical activity, and symptoms that improve their treatment adherence. Moreover, AI-powered education can engage patients through 24/7 support. In research, AI enables the discovery of novel risk factors and treatment targets. Therefore, large opportunities exist to embed AI into pediatric kidney stone management and create value in care and outcomes, for which further research and investment is necessary.}, number={1}, publisher={Samsun University}