ArticleDiagnostics (Basel, Switzerland)2023
Comparison of Machine Learning Models and the Fatty Liver Index in Predicting Lean Fatty Liver.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 10 citations in OpenAlex.
- Hepatic Steatosis Severity Prediction in Nonobese Individuals: Machine Learning Model Development and Validation.Journal of medical Internet research · 2026Article
- Article
- Attention-based graph neural network framework for non-invasive CAP score prediction in fatty liver disease via body modeling.Physical and engineering sciences in medicine · 2026Article
- Development of a Neural Network to Detect Hepatic Steatosis in Metabolic Dysfunction-Associated Steatotic Liver Disease.Gastro hep advances · 2026Article
- Prediction of Metabolic Dysfunction-Associated Steatotic Liver Disease via Advanced Machine Learning Among Chinese Han Population.Obesity surgery · 2025Article
- Predicting the risk of lean non-alcoholic fatty liver disease based on interpretable machine models in a Chinese T2DM population.Frontiers in endocrinology · 2025Article
- Investigation of predictive factors for fatty liver in children and adolescents using artificial intelligence.Frontiers in pediatrics · 2025Article
- LASSO-derived model for the prediction of lean-non-alcoholic fatty liver disease in examinees attending a routine health check-up.Annals of medicine · 2024Article
- Nomogram for predicting 5-year metabolic dysfunction-associated steatotic liver disease risk: retrospective cohort study.Endocrine connections · 2024Article
- Precision Non-Alcoholic Fatty Liver Disease (NAFLD) Diagnosis: Leveraging Ensemble Machine Learning and Gender Insights for Cost-Effective Detection.Bioengineering (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
The reported prevalence of non-alcoholic fatty liver disease in studies of lean individuals ranges from 7.6% to 19.3%. The aim of the study was to develop machine-learning models for the prediction of fatty liver disease in lean individuals. The present retrospective study included 12,191 lean subjects with a body mass index < 23 kg/m
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.