ArticleJournal of personalized medicine2022
Predicting the Risk of Incident Type 2 Diabetes Mellitus in Chinese Elderly Using Machine Learning Techniques.
Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis.Frontiers in digital health · 2025Pooled it
- Review
- Sex-specific machine learning models for carotid plaque prediction in individuals with fatty liver disease: a cross-sectional study.BMJ open · 2026Article
- Machine-learning-based prediction model of type 2 diabetes using liver enzymes: a cross-sectional study.Frontiers in endocrinology · 2026Article
- Associations between peripheral neuropathy and cardiovascular complications in patients with type 2 diabetes mellitus: a cross-sectional study.Scientific reports · 2025Article
- Performance of diabetes risk prediction models: a systematic review and meta-analysis.Endocrine connections · 2025Article
- Type 2 Diabetes Prediction Model in China: A Five-Year Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Diabetic peripheral neuropathy detection of type 2 diabetes using machine learning from TCM features: a cross-sectional study.BMC medical informatics and decision making · 2025Observational
- Survey-Based Machine Learning Models for Early Detection of Diabetes.The 7th International Conference on Wireless, Intelligent and Distributed Environment for Communication : WIDECOM 2024. International Conference on Wireless, Intelligent and Distributed Environment for Communication (7th : 2024 : Keene,... · 2025Article
- Stacking model framework reveals clinical biochemical data and dietary behavior features associated with type 2 diabetes: A retrospective cohort study.APL bioengineering · 2024Article
- Factors associated with acquiring exercise habits through health guidance for metabolic syndrome among middle-aged Japanese workers: A machine learning approach.Preventive medicine reports · 2024Article
- Leveraging Shapley Additive Explanations for Feature Selection in Ensemble Models for Diabetes Prediction.Bioengineering (Basel, Switzerland) · 2024Article
- Predicting diabetes in adults: identifying important features in unbalanced data over a 5-year cohort study using machine learning algorithm.BMC medical research methodology · 2024Article
- Exploring Predictive Factors for Heart Failure Progression in Hypertensive Patients Based on Medical Diagnosis Data from the MIMIC-IV Database.Bioengineering (Basel, Switzerland) · 2024Article
- Integrated bagging-RF learning model for diabetes diagnosis in middle-aged and elderly population.PeerJ. Computer science · 2024Article
- Artificial Intelligence Application for Anti-tumor Drug Synergy Prediction.Current medicinal chemistry · 2024Review
- Environmental exposures in machine learning and data mining approaches to diabetes etiology: A scoping review.Artificial intelligence in medicine · 2023Article
- Machine learning models for predicting the risk factor of carotid plaque in cardiovascular disease.Frontiers in cardiovascular medicine · 2023Article
- Utilization of artificial intelligence in clinical practice: A systematic review of China's experiences.Digital healthReview
- Review: Machine learning in precision pharmacotherapy of type 2 diabetes-A promising future or a glimpse of hope?Digital healthReview
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Early identification of individuals at high risk of diabetes is crucial for implementing early intervention strategies. However, algorithms specific to elderly Chinese adults are lacking. The aim of this study is to build effective prediction models based on machine learning (ML) for the risk of type 2 diabetes mellitus (T2DM) in Chinese elderly. A retrospective cohort study was conducted using the health screening data of adults older than 65 years in Wuhan, China from 2018 to 2020. With a strict data filtration, 127,031 records from the eligible participants were utilized. Overall, 8298 participants were diagnosed with incident T2DM during the 2-year follow-up (2019-2020). The dataset was randomly split into training set (
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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 Socratic graph.