Machine learning-based prediction model for arteriovenous fistula thrombosis risk: a retrospective cohort study from 2017 to 2024

Machine learning-based prediction model for arteriovenous fistula thrombosis risk: a retrospective cohort study from 2017 to 2024

Abstract Background Thrombosis of arteriovenous fistulas represents a prevalent complication among patients undergoing hemodialysis, characterized by a notably high incidence rate. Presently, there is an absence of robust assessment tools capable of predicting thrombosis occurrence. This study seeks...

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Bibliographic Details
Main Authors: Peng Shu, Ling Huang, Xia Wang, Zhuping Wen, Yiqi Luo, Fang Xu
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Nephrology
Subjects:
Machine learning
Arteriovenous fistula
Thrombosis
Prediction model
Online Access:https://doi.org/10.1186/s12882-025-04201-4
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