Last Posted: Jan 05, 2023
- Prevalence of prediabetes and associated factors of prediabetic stages: a cross-sectional study among adults in Nepal.
Shakya Pushpanjali et al. BMJ open 2022 12(12) e064516
- Testing the Utility of Polygenic Risk Scores for Type 2 Diabetes and Obesity in Predicting Metabolic Changes in a Prediabetic Population: An Observational Study.
Padilla-Martinez Felipe et al. International journal of molecular sciences 2022 23(24)
- MicroRNAs Associated with Incident Diabetes in the Diabetes Prevention Program.
Flowers Elena et al. The Journal of clinical endocrinology and metabolism 2022
- Personalised prevention of type 2 diabetes.
Wareham Nicholas J et al. Diabetologia 2022
- Predicting the 2-Year Risk of Progression from Prediabetes to Diabetes Using Machine Learning among Chinese Elderly Adults.
Liu Qing et al. Journal of personalized medicine 2022 12(7)
- Machine Learning for Predicting the Risk of Transition from Prediabetes to Diabetes.
Zueger Thomas et al. Diabetes technology & therapeutics 2022
- A Polygenic Score for Type 2 Diabetes Improves Risk Stratification Beyond Current Clinical Screening Factors in an Ancestrally Diverse Sample.
Ashenhurst James R et al. Frontiers in genetics 2022 13871260
- Identification of Prediabetes Discussions in Unstructured Clinical Documentation: Validation of a Natural Language Processing Algorithm.
Schwartz Jessica L et al. JMIR medical informatics 2022 10(2) e29803
- Research on physical activity variability and changes of metabolic profile in patients with prediabetes using Fitbit activity trackers data.
Bliudzius Antanas et al. Technology and health care : official journal of the European Society for Engineering and Medicine 2021
- An Electronic Health Record-Compatible Model to Predict Personalized Treatment Effects From the Diabetes Prevention Program: A Cross-Evidence Synthesis Approach Using Clinical Trial and Real-World Data.
Kent David M et al. Mayo Clinic proceedings 2021
- Exploration of Machine Learning and Statistical Techniques in Development of a Low-Cost Screening Method Featuring the Global Diet Quality Score for Detecting Prediabetes in Rural India.
Birk Nick et al. The Journal of nutrition 2021 151(Supplement_2) 110S-118S
- Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study.
van Doorn William P T M et al. PloS one 2021 16(6) e0253125
- Predicting youth diabetes risk using NHANES data and machine learning.
Vangeepuram Nita et al. Scientific reports 2021 11(1) 11212
- Establishment of noninvasive diabetes risk prediction model based on tongue features and machine learning techniques.
Li Jun et al. International journal of medical informatics 2021 149104429
- A tongue features fusion approach to predicting prediabetes and diabetes with machine learning.
Li Jun et al. Journal of biomedical informatics 2021 Feb 103693
- Early Detection of Prediabetes and T2DM Using Wearable Sensors and Internet-of-Things-Based Monitoring Applications
MM Baig et al, Appl Clin Informatics, January 2021
- Pathophysiology-based subphenotyping of individuals at elevated risk for type 2 diabetes
R Wagner et al, Nature Medicine, January 4, 2021
- PRISQ: a simple risk score to screen for prediabetes: a cross-sectional study from the Qatar Biobank Cohort.
Abbas Mostafa et al. Journal of diabetes investigation 2020 Oct
- Artificial Intelligence Uncovered Clinical Factors for Cardiovascular Events in Myocardial Infarction Patients with Glucose Intolerance.
Shindo Kazuhiro et al. Cardiovascular drugs and therapy 2020 May
- A combined strategy of feature selection and machine learning to identify predictors of prediabetes.
De Silva Kushan et al. Journal of the American Medical Informatics Association : JAMIA 2019 Dec
Diabetes PHGKB is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other materials that address the translation of genomic and other precision health discoveries into improved health care and prevention related to diabetes...more
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Disclaimer: Articles listed in the Public Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.