Last Posted: Mar 01, 2022
- 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
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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.