BACKGROUND: Large language models (LLMs), such as ChatGPT, have demonstrated promising potential in medical knowledge retrieval and clinical decision support. DeepSeek, a China-developed model released in 2025, has been proposed as a medical AI tool,...
BACKGROUND: Urolithiasis, particularly anhydrous uric acid stones (AUAs), imposes significant clinical and economic burdens. Accurate preoperative differentiation of AUAs from other stone types remains challenging, yet essential for personalized pati...
INTRODUCTION: The current systematic review aims to summarize the existing data on intraoperative use of artificial intelligence (AI) during endoscopic lithotripsy in order to assess which particular applications are feasible and have prospects of wi...
The Urologic clinics of North America
May 22, 2025
Stone disease management is continuously evolving through the introduction of novel tools and technologies. Artificial intelligence and machine learning (ML) promise a new technological frontier for the enhancement of urolithiasis diagnosis, treatmen...
BACKGROUND: Urolithiasis, a prevalent condition characterized by a high rate of incidence and recurrence, necessitates accurate preoperative diagnostic methods to determine stone composition for effective clinical management. Current diagnostic pract...
BACKGROUND AND OBJECTIVE: Our aim was to develop an artificial intelligence (AI) system for detection of urolithiasis in computed tomography (CT) images using advanced deep learning capable of real-time calculation of stone parameters such as volume ...
This research presents our application of artificial intelligence (AI) in predicting urolithiasis risk. Previous applications, including AI for stone disease, have focused on stone composition and aiding diagnostic imaging. AI applications centered a...
OBJECTIVES: Artificial intelligence (AI) applications are increasingly being utilized by both patients and physicians for accessing medical information. This study focused on the urolithiasis section (pertaining to kidney and ureteral stones) of the ...
PURPOSE: Urolithiasis is a chronic condition that leads to repeated CT scans throughout the patient's life. The goal was to assess the diagnostic performance and image quality of submillisievert abdominopelvic computed tomography (CT) using deep lear...
We attempted to determine the optimal radiation dose to maintain image quality using a deep learning application in a physical human phantom. Three 5 × 5 × 5 mm uric acid stones were placed in a physical human phantom in various locations. Three tu...
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