Predictive machine learning model in intensive care unit patients with acute-on-chronic liver failure and two or more organ failures

We presented explainable, well-validated, and calibrated predictive models for ACLF patients with two or more OFs, which outperformed existing predictive scores.

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Publication Details

Journal
Clinical and Molecular Hepatology
Published
2025-09-02
DOI
https://doi.org/10.3350/cmh.2025.0573
Citations
1
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
2.94

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article

Predictive machine learning model in intensive care unit patients with acute-on-chronic liver failure and two or more organ failures

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1 citations
Clinical and Molecular Hepatology
Artificial Intelligence in Healthcare
2.94
article

Predictive machine learning model in intensive care unit patients with acute-on-chronic liver failure and two or more organ failures

Xiaodan Sun, Hirsh D. Trivedi, Yee Hui Yeo, Soo Young Hwang, Jonel Trebicka, M. McCoy, Zhujun Cao, Fanpu Ji, Vinay Sundaram, Jian Zu, Mingjie Zhang, Juan Li, Yuan Wang, Yingli He, Chun-Ying Wu, Taotao Yan, Yi Liu
article en
1 citations

Abstract

We presented explainable, well-validated, and calibrated predictive models for ACLF patients with two or more OFs, which outperformed existing predictive scores.

Clinical and Molecular HepatologyVol. 31(4)
Cedars-Sinai Medical Center (US), National Yang Ming Chiao Tung University (TW), Shanghai Jiao Tong University (CN), China Medical University (TW), University of Münster (DE), Odense University Hospital (DK), Ruijin Hospital (CN), Taipei Veterans General Hospital (TW), European Foundation for the Study of Chronic Liver Failure (ES), First Affiliated Hospital of Xi'an Jiaotong University (CN), Second Affiliated Hospital of Xi'an Jiaotong University (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 7%
Artificial Intelligence in Healthcare
2.94
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