Novel machine learning models for the prediction of acute respiratory distress syndrome after liver transplantation

Novel machine learning models for the prediction of acute respiratory distress syndrome after liver transplantation

Early prediction of acute respiratory distress syndrome (ARDS) after liver transplantation (LT) facilitates timely intervention. We aimed to develop a predictor of post-LT ARDS using machine learning (ML) methods. Data from 755 patients in the internal validation set and 115 patients in the external...

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Bibliographic Details
Main Authors: Weijie Wu, Zheng Zhang, Shuailei Wang, Ru Xin, Dong Yang, Weifeng Yao, Ziqing Hei, Chaojin Chen, Gangjian Luo
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Artificial Intelligence
Subjects:
liver transplantation
acute respiratory distress syndrome
machine learning
prediction model
random forest
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2025.1548131/full
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https://www.frontiersin.org/articles/10.3389/frai.2025.1548131/full

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