AIMC Topic: Lithotripsy
Clear Filters Showing 1 to 10 of 18 articles
Current state of AI for shockwave lithotripsy: a systematic review from YAU and EAU endourology.
World journal of urology
Jul 11, 2025
PURPOSE: To consolidate the current evidence of artificial intelligence (AI) for management of nephrolithiasis using extracorporeal shock-wave lithotripsy (ESWL), and to look at its feasibility into integration in clinical practice.
Predicting ESWL success for ureteral stones: a radiomics-based machine learning approach.
BMC medical imaging
Jul 4, 2025
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model that integrates radiomics and conventional radiological features to predict the success of single-session extracorporeal shock wave lithotripsy (ESWL) for ureteral sto...
Artificial Intelligence and Machine Learning for Stone Management.
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...
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...
CT-based deep learning model for predicting the success of extracorporeal shock wave lithotripsy in treating ureteral stones larger than 1 cm.
Urolithiasis
Nov 5, 2024
OBJECTIVES: To develop a deep learning (DL) model based on computed tomography (CT) images to predict the success of extracorporeal shock wave lithotripsy (SWL) treatment for patients with ureteral stones larger than 1 cm.
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.
Using ensemble learning and hierarchical strategy to predict the outcomes of ESWL for upper ureteral stone treatment.
Computers in biology and medicine
Jul 23, 2024
Urinary tract stones are a common and frequently recurring medical issue. Accurately predicting the success rate after surgery can help avoid ineffective medical procedures and reduce unnecessary healthcare costs. This study collected data from patie...
Predicting the Efficacy of Repeated Shockwave Lithotripsy for Treating Patients with Upper Urinary Tract Calculi Using an Artificial Neural Network Model.
Urology journal
Jun 9, 2024
PURPOSE: To establish a prediction model for repeated shockwave lithotripsy (SWL) efficacy to help choose an appropriate treatment plan for patients with a single failed lithotripsy, reducing their treatment burden.
Image Enhancement Model Based on Deep Learning Applied to the Ureteroscopic Diagnosis of Ureteral Stones during Pregnancy.
Computational and mathematical methods in medicine
Oct 29, 2021
OBJECTIVE: To explore the image enhancement model based on deep learning on the effect of ureteroscopy with double J tube placement and drainage on ureteral stones during pregnancy. We compare the clinical effect of ureteroscopy with double J tube pl...
Machine Learning Models for Predicting Stone-Free Status after Shockwave Lithotripsy: A Systematic Review and Meta-Analysis.
Urology
Apr 21, 2021
We performed a systematic review and meta-analysis to investigate the use of machine learning techniques for predicting stone-free rates following Shockwave Lithotripsy (SWL). Eight papers (3264 patients) were included. Two studies used decision-tree...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31964
- Neural Networks, Computer 30201
- Algorithms 27375
- Deep Learning 26880
- Artificial Intelligence 24817
- Robotics 13382
- Image Processing, Computer-Assisted 9730
- Retrospective Studies 9328
- Magnetic Resonance Imaging 6341
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4863
- Support Vector Machine 4762
- Computational Biology 4328
- Brain 4125
- Computer Simulation 3932
Recent Journals
- Scientific reports 6689
- Sensors (Basel, Switzerland) 4794
- PloS one 4186
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1915
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1167
- Journal of chemical information and modeling 1059
- Nature communications 1029
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 872
- Journal of medical Internet research 853
- Briefings in bioinformatics 853