Machine learning for predicting all-cause mortality of metabolic dysfunction-associated fatty liver disease: a longitudinal study based on NHANES
Machine learning has a promising application in predicting all-cause mortality in MAFLD individuals. Combined the results of interpretable machine learning and association analyses, we found risk factors which contributing to the all-cause mortality. These findings provide insights for community health practitioners to intervene in modifiable risk factors, thereby improving the survival and quality of life of MAFLD individuals.
Authors
- X. Wang
- Luqiao Wang (ORCID: https://orcid.org/0000-0003-0263-9492)
- Wenguang Sun (ORCID: https://orcid.org/0000-0002-1808-8106)
- Huihui Chen (ORCID: https://orcid.org/0000-0003-1040-4351)
Institutions
- Second Affiliated Hospital of Zhejiang University (CN)
Publication Details
- Journal
- BMC Gastroenterology
- Published
- 2025-05-15
- DOI
- https://doi.org/10.1186/s12876-025-03946-4
- Citations
- 4
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 5.42