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May 22, 2024European Urology Open ScienceOpen Access

Can Machine Learning Correctly Predict Outcomes of Flexible Ureteroscopy with Laser Lithotripsy for Kidney Stone Disease? Results from a Large Endourology University Centre

Carlotta Nedbal Sairam Adithya Nithesh Naik Shilpa Gite Patrick Juliebø‐Jones Bhaskar Somani

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Abstract

The integration of machine learning (ML) in health care has garnered significant attention because of its unprecedented opportunities to enhance patient care and outcomes. In this study, we trained ML algorithms for automated prediction of outcomes of ureteroscopic laser lithotripsy (URSL) on the basis of preoperative characteristics.

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Cite This Study

Nedbal et al. (2024) studied this question.

synapsesocial.com/papers/68e68e6fb6db6435876153e6 https://doi.org/10.1016/j.euros.2024.05.004

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1A Machine Learning (ML) Predictive Model for Ureteroscopy lasertripsy (URSL) Outcomes in a Paediatric Population – Results from a large Endourology Tertiary Centre2024 · 8 citations
2Efficacy and safety of ureteroscopy in children with lower pole renal stones – a machine learning predictive model from the EAU section of Endourology2025
3Machine learning to predict ureteral access sheath placement failure in flexible ureteroscopy: development and prospective validationCohort Study · 2026
4Machine learning-based screening of characteristic factors for urinary tract infection following ureteral stone surgery and construction and validation of risk prediction models2025
5Machine learning analysis of CT images for the prediction of extracorporeal shock wave lithotripsy efficacy2024 · 1 citations

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Machine learning for early prediction of the infection in patients with urinary stone after treatment of holmium laser lithotripsy2025
Machine Learning-Based Integration of Multiple Indicators to Predict Ureteral Access Sheath Placement Failure During Flexible Ureteroscopic Lithotripsy2025
Stone decision engine accurately predicts stone removal and treatment complications for shock wave lithotripsy and laser ureterorenoscopy patients2024

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