Crossmark

Survival machine learning models for predicting all-cause and case-specific mortality risk in metabolic dysfunction-associated fatty liver disease patients

Crossref DOI link: https://doi.org/10.1038/s41598-025-26729-z

Published Online: 2025-11-28

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Gao, Jingpeng

Zhang, Nan

Aximu, Akemujiang

Xin, Ning

Wang, Ziwei

Yan, Ping
Funding

Funding for this research was provided by:

State Key Laboratory of Pathogenesis, Prevention, Treatment of Central Asian High Incidence Diseases Fund (SKL-HIDCA-2023-HL-12)

Regional Collaborative Innovation Special Project of Autonomous Region - Science and Technology Aid Xinjiang Plan (2022E02119)

Xinjiang Medical University Intelligent Aging Care and Integrative Care for Older Adults Innovation Research Team (XYD2024C06)
License Information

Text and Data Mining valid from 2025-11-28

Version of Record valid from 2025-11-28
More Information

Article History

Received: 31 May 2025

Accepted: 30 October 2025

First Online: 28 November 2025

Declarations

:

: The authors declare no competing interests.

: Ethical approval for NHANES was secured from the NCHS Research Ethics Review Board, and each participant willingly provided written informed consent.

Document is current

Any future updates will be listed below