ArticleJournal of diabetes research2020
Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.
Article in Journal of diabetes research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Predicting incident type 2 diabetes using wearable activity and polygenic risk: A survival-modeling study in All of Us.The Journal of clinical endocrinology and metabolism · 2026Article
- Machine Learning Unveils Dietary Antioxidants as Influential Factors for Diabetes-Cancer Comorbidity: Insights From National Health and Nutrition Examination Survey.Food science & nutrition · 2026Article
- Development and comparative evaluation of machine learning algorithms and Cox regression for predicting fasting plasma glucose-defined incident prediabetes: a longitudinal cohort study.Frontiers in endocrinology · 2026Article
- Development of a 5-Year Risk Prediction Model for Transition From Prediabetes to Diabetes Using Machine Learning: Retrospective Cohort Study.Journal of medical Internet research · 2025Article
- Stacking model framework reveals clinical biochemical data and dietary behavior features associated with type 2 diabetes: A retrospective cohort study.APL bioengineering · 2024Article
- Automated sample annotation for diabetes mellitus in healthcare integrated biobanking.Computational and structural biotechnology journal · 2024Article
- Development and Validation of Machine Learning Models for Identifying Prediabetes and Diabetes in Normoglycemia.Diabetes/metabolism research and reviews · 2024Article
- Predicting three-month fasting blood glucose and glycated hemoglobin changes in patients with type 2 diabetes mellitus based on multiple machine learning algorithms.Scientific reports · 2023Article
- Environmental exposures in machine learning and data mining approaches to diabetes etiology: A scoping review.Artificial intelligence in medicine · 2023Article
- Design of predictive model to optimize the solubility of Oxaprozin as nonsteroidal anti-inflammatory drug.Scientific reports · 2022Article
- Predicting the 2-Year Risk of Progression from Prediabetes to Diabetes Using Machine Learning among Chinese Elderly Adults.Journal of personalized medicine · 2022Article
- Predicting the Risk of Incident Type 2 Diabetes Mellitus in Chinese Elderly Using Machine Learning Techniques.Journal of personalized medicine · 2022Article
- Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation.Frontiers in public health · 2022Article
- A Noninvasive Prediction Model for Hepatitis B Virus Disease in Patients with HIV: Based on the Population of Jiangsu, China.BioMed research international · 2021Article
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5 authors.
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Abstract
backgroundAn estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas.
methodsA total of 584,168 adult subjects who have participated in the national physical examination were enrolled in this study. The risk factors for type II diabetes mellitus (T2DM) were identified by
resultsThe results indicated that XGBoost had the best performance (accuracy = 0.906, precision = 0.910, recall = 0.902,
conclusionsWe proposed a classifier based on LR-XGBoost which used fourteen variables of patients which are easily obtained and noninvasive as predictor variables to identify potential incidents of T2DM. The classifier can accurately screen the risk of diabetes in the early phrase, and the degree of variables' importance scores gives a clue to prevent diabetes occurrence.
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