This paper is in the following e-collection/theme issue:

Methods and Instruments in Medical Informatics (204) Clinical Informatics (1370) Machine Learning (2148) Advanced Data Analytics in eHealth (219) Tools, Programs and Algorithms (392) Computer-Aided Diagnosis (266)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/75747, first published .
Predicting Metabolic Dysfunction–Associated Fatty Liver Disease Phenotypes Among Adults: 2-Stage Contrastive Learning Method

Predicting Metabolic Dysfunction–Associated Fatty Liver Disease Phenotypes Among Adults: 2-Stage Contrastive Learning Method

Predicting Metabolic Dysfunction–Associated Fatty Liver Disease Phenotypes Among Adults: 2-Stage Contrastive Learning Method

Authors of this article:

Sizhe Jasmine Chen1 Author Orcid Image ;   Da Xu2 Author Orcid Image ;   Derek K Hu3 Author Orcid Image ;   Paul Jen-Hwa Hu1 Author Orcid Image ;   Ting-Shuo Huang4, 5, 6 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Feng T, Li Y, Feng Y, Zeng C. Application of emerging information technologies in the prevention and control of chronic diseases. Frontiers in Public Health 2026;14 View