Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy

Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy

Abstract 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 construct a machine learning algorithm predictive...

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Bibliographic Details
Main Authors: Haofang Zhang, Changbao Xu, Chenge Hu, Yunlai Xue, Daoke Yao, Yifan Hu, Ankang Wu, Miao Dai, Hang Ye
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Flexible ureteroscopy lithotripsy
Machine learning algorithms
Fungal infection
Risk factors
XGBoost model
Online Access:https://doi.org/10.1186/s12911-025-02987-9
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