AIMC Topic: Urolithiasis
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Development and evaluation of USCnet: an AI-based model for preoperative prediction of infectious and non-infectious urolithiasis.
World journal of urology
Feb 27, 2025
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...
A Novel Deep Learning-based Artificial Intelligence System for Interpreting Urolithiasis in Computed Tomography.
European urology focus
Jul 12, 2024
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 ...
Artificial Intelligence in Urology: Application of a Machine Learning Model to Predict the Risk of Urolithiasis in a General Population.
Journal of endourology
Jul 4, 2024
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...
Comparative analysis of artificial intelligence chatbot recommendations for urolithiasis management: A study of EAU guideline compliance.
The French journal of urology
Jun 5, 2024
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 ...
Detection of urinary tract stones on submillisievert abdominopelvic CT imaging with deep-learning image reconstruction algorithm (DLIR).
Abdominal radiology (New York)
Mar 12, 2024
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...
Dose Optimization Using a Deep Learning Tool in Various CT Protocols for Urolithiasis: A Physical Human Phantom Study.
Medicina (Kaunas, Lithuania)
Sep 17, 2023
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...
Fully Automated Longitudinal Assessment of Renal Stone Burden on Serial CT Imaging Using Deep Learning.
Journal of endourology
Jun 30, 2023
Use deep learning (DL) to automate the measurement and tracking of kidney stone burden over serial CT scans. This retrospective study included 259 scans from 113 symptomatic patients being treated for urolithiasis at a single medical center between...
Prediction of the composition of urinary stones using deep learning.
Investigative and clinical urology
May 25, 2022
PURPOSE: This study aimed to predict the composition of urolithiasis using deep learning from urinary stone images.
Machine Learning-Assisted Preoperative Diagnosis of Infection Stones in Urolithiasis Patients.
Journal of endourology
Apr 28, 2022
The decision-making of how to treat urinary infection stones was complicated by the difficulty in preoperative diagnosis of these stones. Hence, we developed machine learning (ML) models that can be leveraged to discriminate between infection and no...
Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis.
European radiology
Mar 31, 2022
OBJECTIVES: To determine the diagnostic accuracy and image quality of ultra-low-dose computed tomography (ULDCT) with deep learning reconstruction (DLR) to evaluate patients with suspected urolithiasis, compared with ULDCT with hybrid iterative recon...
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