Effectiveness of artificial intelligence screening in preventing vision loss from diabetes: a policy model.
Roomasa Channa et al. NPJ digital medicine 2023 3 (1) 53
Evaluation of polygenic risk scores to differentiate between type 1 and type 2 diabetes.
Muhammad Shoaib et al. Genetic epidemiology 2023 2
Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges.
Shuai Yuan et al. Diabetologia 2023 2
Beyond genetic screening-functionality-based precision medicine in monogenic obesity.
Antje Körner et al. The lancet. Diabetes & endocrinology 2023 2 (3) 143-144
Zang Chengxi, et al. Research square 2023 0 0.
A machine learning approach for early prediction of gestational diabetes mellitus using elemental contents in fingernails.
Yun-Nam Chan et al. Scientific reports 2023 13(1) 4184
Implementation of deep learning artificial intelligence in vision-threatening disease screenings for an underserved community during COVID-19.
Aretha Zhu et al. Journal of telemedicine and telecare 2023 1357633X231158832
The Effectiveness of Wearable Devices Using Artificial Intelligence for Blood Glucose Level Forecasting or Prediction: Systematic Review.
Arfan Ahmed et al. Journal of medical Internet research 2023 25e40259
The severity of COVID-19 in hypertensive patients is associated with mirSNPs in the 3' UTR of ACE2 that associate with miR-3658: In silico and in vitro studies.
Safdar Muhammad, et al. Journal of Taibah University Medical Sciences 2023 0 0. (5) 1030-1047
Association of triglyceride-glucose index with atherosclerotic cardiovascular disease and mortality among familial hypercholesterolemia patients.
Jun Wen et al. Diabetology & metabolic syndrome 2023 15(1) 39
Clinical Spectrum of LMNA-Associated Type 2 Familial Partial Lipodystrophy: A Systematic Review.
Antia Fernandez-Pombo et al. Cells 2023 12(5)
Hyperglycemia in Turner syndrome: Impact, mechanisms, and areas for future research.
Cameron Mitsch et al. Frontiers in endocrinology 2023 141116889
Nonalcoholic fatty liver disease (NAFLD) detection and deep learning in a Chinese community-based population.
Yang Yang et al. European radiology 2023
Prediction of the risk of developing end-stage renal diseases in newly diagnosed type 2 diabetes mellitus using artificial intelligence algorithms.
Shuo-Ming Ou et al. BioData mining 2023 16(1) 8
About Diabetes PHGKB
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.
- Page last reviewed:Feb 1, 2023
- Page last updated:Mar 28, 2023
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