AIMC Topic: Kidney Calculi

Clear Filters Showing 61 to 70 of 77 articles

Predictors and associations of complications in ureteroscopy for stone disease using AI: outcomes from the FLEXOR registry.

Urolithiasis
We aimed to develop machine learning(ML) algorithms to evaluate complications of flexible ureteroscopy and laser lithotripsy(fURSL), providing a valid predictive model. 15 ML algorithms were trained on a large number fURSL data from > 6500 patients f...

High-frequency in laser lithotripsy: do we truly know what it means?

World journal of urology
INTRODUCTION AND OBJECTIVE: High frequency (HF) in laser lithotripsy lacks a consistent definition, potentially impacting clinical outcomes and patient safety. This review aims to analyze available evidence on the definition of HF.

AI-Augmented Kidney Stone Composition Analysis with Auto-Release Improves Quality, Efficiency, Cost-Effectiveness, and Staff Satisfaction.

The journal of applied laboratory medicine
BACKGROUND: We sought to evaluate key performance indicators related to an internally developed and deployed artificial intelligence (AI)-augmented kidney stone composition test system for potential improvements in test quality, efficiency, cost-effe...

[Identification of kidney stone types by deep learning integrated with radiomics features].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Currently, the types of kidney stones before surgery are mainly identified by human beings, which directly leads to the problems of low classification accuracy and inconsistent diagnostic results due to the reliance on human knowledge. To address thi...

A Novel Machine-Learning Algorithm to Predict Stone Recurrence with 24-Hour Urine Data.

Journal of endourology
The absence of predictive markers for kidney stone recurrence poses a challenge for the clinical management of stone disease. The unpredictability of stone events is also a significant limitation for clinical trials, where many patients must be enro...

[Construction of a back propagation neural network model for predicting urosepsis after flexible ureteroscopic lithotripsy].

Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences
OBJECTIVES: To analyze the association of serum heparin-binding protein (HBP) and C-reactive protein (CRP) levels with urosepsis following flexible ureteroscopic lithotripsy (FURL) and to construct a back propagation neural network prediction model.

Initial experience with robot-assisted ureteroscopy with Ily® Robot.

Minerva urology and nephrology
The aim of this study is to present the first Italian experience with robotic-assisted retrograde intrarenal surgery (rRIRS) using the Ily platform. Procedures were performed for renal stones using the Ily Robot (STERLAB, Vallauris, France), which is...

Robot-assisted anatrophic nephrolithotomy for complete staghorn stone.

Medicine
To assess the efficacy and safety of robot-assisted anatrophic nephrolithotomy (RANL) as a choice of minimally invasive treatment for patients with complete staghorn stone. In a single-tertiary referral center retrospective study, 10 consecutive pati...