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References from Machine-learning-based prediction model of type 2 diabetes using liver enzymes: a cross-sectional study. Local targets link to admitted publications; unresolved targets remain external evidence.
Idf diabetes atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045
10.1016/j.diabres.2021.109119 · 2022 · External reference
Risk of cause-specific death in individuals with diabetes: a competing risks analysis
10.2337/dc16-0614 · 2016 · External reference
Global aetiology and epidemiology of type 2 diabetes mellitus and its complications
10.1038/nrendo.2017.151 · 2018 · External reference
Artificial intelligence and machine learning in clinical medicine
10.1056/nejmc2305287 · 2023 · External reference
Machine learning and deep learning predictive models for type 2 diabetes: a systematic review
10.1186/s13098-021-00767-9 · 2021 · External reference
10.1016/j.csbj.2016.12.005 · 2017 · Admitted local publication
Building risk prediction models for type 2 diabetes using machine learning techniques
10.5888/pcd16.190109 · 2019 · External reference
Prediction of type 2 diabetes based on machine learning algorithm
10.3390/ijerph18063317 · 2021 · External reference
Predicting type 2 diabetes using logistic regression and machine learning approaches
10.3390/ijerph18147346 · 2021 · External reference
Machine learning models in type 2 diabetes risk prediction: results from a cross-sectional retrospective study in Chinese adults
10.1007/s11596-019-2077-4 · 2019 · External reference
Prediction model for type 2 diabetes mellitus and its association with mortality using machine learning in three independent cohorts from South Korea, Japan, and the UK: a model development and validation study
10.1016/j.eclinm.2025.103069 · 2025 · External reference
Prediction of type 2 diabetes using genome-wide polygenic risk score and metabolic profiles: a machine learning analysis of population-based 10-year prospective cohort study
10.1016/j.ebiom.2022.104383 · 2022 · External reference
Environmental chemical exposure dynamics and machine learning-based prediction of diabetes mellitus
10.1016/j.scitotenv.2021.150674 · 2022 · External reference
A machine learning-based diagnosis modelling of type 2 diabetes mellitus with environmental metal exposure
10.1016/j.cmpb.2023.107537 · 2023 · External reference
Association between liver enzymes and incident type 2 diabetes in Singapore Chinese men and women
10.1136/bmjdrc-2016-000296 · 2016 · External reference
Liver enzymes, fatty liver and type 2 diabetes mellitus in a Jinchang cohort: a prospective study in adults
10.1016/j.jcjd.2018.02.002 · 2018 · External reference
Association between liver enzymes and type 2 diabetes: a real-world study
10.3389/fendo.2024.1340604 · 2024 · External reference
The relationship between hepatic enzymes, prediabetes, and diabetes in the Azar cohort population
10.1186/s12902-025-01871-x · 2025 · External reference
Elevated liver enzymes and diabetes in the Persian Guilan cohort study
10.22088/cjim.16.1.73 · 2025 · External reference
The different associations of serum gamma-glutamyl transferase and alanine aminotransferase with insulin secretion, β-cell function, and insulin resistance in non-obese Japanese
10.1038/s41598-024-70396-5 · 2024 · External reference
A calibration hierarchy for risk models was defined: from utopia to empirical data
10.1016/j.jclinepi.2015.12.005 · 2016 · External reference
Reporting and interpreting decision curve analysis: a guide for investigators
10.1016/j.eururo.2018.08.038 · 2018 · External reference
Nonlaboratory-based risk assessment algorithm for undiagnosed type 2 diabetes developed on a nation-wide diabetes survey
10.2337/dc13-0593 · 2013 · External reference
Tripod+ai statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
10.1136/bmj-2023-078378 · 2024 · External reference
A data-driven approach to predicting diabetes and cardiovascular disease with machine learning
10.1186/s12911-019-0918-5 · 2019 · External reference
Machine learning for predicting diabetes risk in Western China adults
10.1186/s13098-023-01112-y · 2023 · External reference
Predicting the risk of incident type 2 diabetes mellitus in Chinese elderly using machine learning techniques
10.3390/jpm12060905 · 2022 · External reference
Gamma-glutamyltransferase: a predictive biomarker of cellular antioxidant inadequacy and disease risk
10.1155/2015/818570 · 2015 · External reference
Gamma-glutamyltransferase-friend or foe within
10.1111/liv.13221 · 2016 · External reference
Mechanistic insight into oxidative stress-triggered signaling pathways and type 2 diabetes
10.3390/molecules27030950 · 2022 · External reference
Liver, muscle, and adipose tissue insulin action is directly related to intrahepatic triglyceride content in obese subjects
10.1053/j.gastro.2008.01.075 · 2008 · External reference
High alanine aminotransferase is associated with decreased hepatic insulin sensitivity and predicts the development of type 2 diabetes
10.2337/diabetes.51.6.1889 · 2002 · External reference
Mitochondrial abnormality and oxidative stress in nonalcoholic steatohepatitis
10.1111/j.1530-0277.2006.00288.x · 2007 · External reference
Global incidence and prevalence of nonalcoholic fatty liver disease
10.3350/cmh.2022.0365 · 2023 · External reference
