Identifying ureteral stent encrustation using machine learning based on CT radiomics features: a bicentric study

Identifying ureteral stent encrustation using machine learning based on CT radiomics features: a bicentric study

ObstructiveTo develop and validate radiomics and machine learning models for identifying encrusted stents and compare their recognition performance with multiple metrics.MethodsA total of 354 patients with ureteral stent placement were enrolled from two medical institutions and divided into the trai...

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Bibliographic Details
Main Authors: Junliang Qiu, Minbo Yan, Haojie Wang, Zicheng Liu, Guojie Wang, Xianbo Wu, Qindong Gao, Hongji Hu, Junyong Chen, Yingbo Dai
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Medicine
Subjects:
ureteral stent encrustation
radiomics
machine learning
artificial intelligence
nomograms
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2023.1202486/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2023.1202486/full

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