Development and validation of a high-performance clinical predictive model for early identification of non-alcoholic fatty liver disease

This study's results confirm the effective creation of an NAFLD predictive tool boasting high calibration accuracy and outstanding performance. Leveraging readily available clinical data, the model offers a scalable, economical approach to NAFLD, poised to pioneer a new paradigm for its precise prevention and control, and enable personalized prevention and efficient resource allocation.

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Publication Details

Journal
Frontiers in Physiology
Published
2026-02-12
DOI
https://doi.org/10.3389/fphys.2026.1689882
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Development and validation of a high-performance clinical predictive model for early identification of non-alcoholic fatty liver disease

Tong Liang, Junli Ren
Frontiers in Physiology
Liver Disease Diagnosis and Treatment
article

Development and validation of a high-performance clinical predictive model for early identification of non-alcoholic fatty liver disease

Tong Liang, Junli Ren
article en

Abstract

This study's results confirm the effective creation of an NAFLD predictive tool boasting high calibration accuracy and outstanding performance. Leveraging readily available clinical data, the model offers a scalable, economical approach to NAFLD, poised to pioneer a new paradigm for its precise prevention and control, and enable personalized prevention and efficient resource allocation.

Frontiers in PhysiologyVol. 17
Gansu University of Traditional Chinese Medicine (CN), Gansu Provincial Maternal and Child Health Hospital (CN)
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 57%
Liver Disease Diagnosis and Treatment
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