ArticleFrontiers in public health2021
Machine Learning for Predicting the 3-Year Risk of Incident Diabetes in Chinese Adults.
Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines 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
- Risk prediction models for incident type 2 diabetes in Chinese people with intermediate hyperglycemia: a systematic literature review and external validation study.Cardiovascular diabetology · 2022Pooled it
- Comprehensive evaluation of the triglyceride glucose index (TyG) and body roundness index (BRI) on cardiovascular disease risk prediction: a 9-year prospective cohort study in Chinese middle-aged and older adults.Cardiovascular diabetology · 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
- Interpretable machine learning method to predict the risk of pre-diabetes using a national-wide cross-sectional data: evidence from CHNS.BMC public health · 2025Article
- AI-based diabetes care: risk prediction models and implementation concerns.NPJ digital medicine · 2024Article
- An artificial neural network model for evaluating the risk of hyperuricaemia in type 2 diabetes mellitus.Scientific reports · 2024Article
- A scoping review of artificial intelligence-based methods for diabetes risk prediction.NPJ digital medicine · 2023Article
- Machine learning for predicting diabetes risk in western China adults.Diabetology & metabolic syndrome · 2023Article
- Artificial Intelligence and Big Data Technologies in the Construction of Surgical Risk Prediction Model for Patients with Coronary Artery Bypass Grafting.Computational intelligence and neuroscience · 2023Article
- Machine learning models for predicting the risk factor of carotid plaque in cardiovascular disease.Frontiers in cardiovascular medicine · 2023Article
- An integrated machine learning predictive scheme for longitudinal laboratory data to evaluate the factors determining renal function changes in patients with different chronic kidney disease stages.Frontiers in medicine · 2023Article
- Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review.Diabetology & metabolic syndrome · 2022Review
- 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
- Analysis of Environmental and Social Significant Factors Affecting the Flow of Maternal Patients in Jilin, China.Frontiers in public health · 2022Article
- Unifying Diagnosis Identification and Prediction Method Embedding the Disease Ontology Structure From Electronic Medical Records.Frontiers in public health · 2021Article
- Prediction of Obstetric Patient Flow and Horizontal Allocation of Medical Resources Based on Time Series Analysis.Frontiers in public health · 2021Article
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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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.