Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome

Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome

BackgroundBudd-Chiari syndrome (BCS) is a rare global condition with high recurrence rates. Existing prognostic scoring models demonstrate limited predictive efficacy for BCS recurrence. This study aims to develop a novel machine learning model based on multiple kernel learning to improve the predic...

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Bibliographic Details
Main Authors: Weirong Xue, Bing Xu, Hui Wang, Xiaoxiao Zhu, Jiajia Qin, Guangshuang Zhou, Peilin Yu, Shengli Li, Yingliang Jin
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Physiology
Subjects:
Budd-Chiari syndrome
recurrence
machine learning
multiple kernel learning
predict
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2025.1589469/full
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https://www.frontiersin.org/articles/10.3389/fphys.2025.1589469/full

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