AIMC Topic: Ureteroscopy
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From laser-on time to lithotripsy duration: improving the prediction of lithotripsy duration with 'Kidney Stone Calculator' using artificial intelligence.
World journal of urology
Jun 26, 2025
INTRODUCTION: "Kidney Stone Calculator" (KSC) helps to plan flexible ureteroscopy, providing the stone volume (SV) and an estimated duration of laser lithotripsy (eLD). eLD is calculated from in vitro ablation rates and SV. KSC's accuracy has been de...
Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy.
BMC medical informatics and decision making
Apr 10, 2025
BACKGROUND: The flexible ureteroscopy lithotripsy (F-URL) is an important treatment for upper urinary tract stones. However, urolithiasis, surgical procedures, and catheter placement are risk factors for fungal infections. Our study aimed to construc...
Measuring kidney stone volume - practical considerations and current evidence from the EAU endourology section.
Current opinion in urology
Feb 21, 2025
PURPOSE OF REVIEW: This narrative review provides an overview of the use, differences, and clinical impact of current methods for kidney stone volume assessment.
Satisfactory Evaluation of Call Service Using AI After Ureteral Stent Insertion: Randomized Controlled Trial.
Journal of medical Internet research
Jan 21, 2025
BACKGROUND: Ureteral stents, such as double-J stents, have become indispensable in urologic procedures but are associated with complications like hematuria and pain. While the advancement of artificial intelligence (AI) technology has led to its incr...
The infection post flexible UreteroreNoscopy (I-FUN) predictive model based on machine learning: a new clinical tool to assess the risk of sepsis post retrograde intrarenal surgery for kidney stone disease.
World journal of urology
Nov 1, 2024
PURPOSE: To create a machine-learning model for estimating the likelihood of post-retrograde intrarenal surgery (RIRS) sepsis.
Letter to the editor for the article "A machine learning approach using stone volume to predict stone-free status at ureteroscopy".
World journal of urology
Aug 22, 2024
A Machine Learning Predictive Model for Ureteroscopy Lasertripsy Outcomes in a Pediatric Population-Results from a Large Endourology Tertiary Center.
Journal of endourology
Aug 12, 2024
We aimed to develop machine learning (ML) algorithms for the automated prediction of postoperative ureteroscopy outcomes for pediatric kidney stones based on preoperative characteristics. Data from pediatric patients who underwent ureteroscopy for ...
Development and validation of a nomogram to predict impacted ureteral stones via machine learning.
Minerva urology and nephrology
Aug 2, 2024
BACKGROUND: To develop and evaluate a nomogram for predicting impacted ureteral stones using some simple and easily available clinical features.
Development of UroSAM: A Machine Learning Model to Automatically Identify Kidney Stone Composition from Endoscopic Video.
Journal of endourology
May 31, 2024
Chemical composition analysis is important in prevention counseling for kidney stone disease. Advances in laser technology have made dusting techniques more prevalent, but this offers no consistent way to collect enough material to send for chemical...
A machine learning approach using stone volume to predict stone-free status at ureteroscopy.
World journal of urology
May 22, 2024
INTRODUCTION: To develop a predictive model incorporating stone volume along with other clinical and radiological factors to predict stone-free (SF) status at ureteroscopy (URS).
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