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Precision Health Database


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Diabetes

Last data update: Aug 12, 2022. (Total: 48803 Documents since 2012)
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Records 1 - 22 (of 22 Records)

Query Trace: Prediabetes[original query]>>Original Studies[Product Type]
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
Early Detection of Prediabetes and T2DM Using Wearable Sensors and Internet-of-Things-Based Monitoring Applications.
Baig Mirza Mansoor et al. Applied clinical informatics 2021 Jan 12(1) 1-9
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
Machine-learning to stratify diabetic patients using novel cardiac biomarkers and integrative genomics.
Hathaway Quincy A et al. Cardiovascular diabetology 2019 Jun 18(1) 78
Feasibility of pediatric obesity and prediabetes treatment support through Tess, the AI behavioral coaching chatbot.
Stephens Taylor N et al. Translational behavioral medicine 2019 May 9(3) 440-447
Precision medicine screening using whole-genome sequencing and advanced imaging to identify disease risk in adults.
Perkins Bradley A et al. Proceedings of the National Academy of Sciences of the United States of America 2018 Mar
The contribution of family history to the burden of diagnosed diabetes, undiagnosed diabetes, and prediabetes in the United States: analysis of the National Health and Nutrition Examination Survey, 2009-2014.
Moonesinghe Ramal, et al. Genetics in medicine : official journal of the American College of Medical Genetics 2018 1 0.
Association of Sickle Cell Trait With Hemoglobin A1c in African Americans.
Lacy Mary E et al. JAMA 2017 Feb 317(5) 507-515
The impact of access to health services on prediabetes awareness: A population-based study.
Campbell Tonya J et al. Preventive medicine 2016 Sep 937-13
The Sangre Por Salud Biobank: Facilitating Genetic Research in an Underrepresented Latino Community.
Shaibi Gabriel et al. Public health genomics 2016 Jul
The risk of type 2 diabetes in men is synergistically affected by parental history of diabetes and overweight.
Family history of diabetes is associated with higher risk for prediabetes: a multicentre analysis from the German Center for Diabetes Research.
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