Gestational Diabetes
What's New
Last Posted: Feb 11, 2022
- Population-centric Risk Prediction Modeling for Gestational Diabetes Mellitus: A Machine Learning Approach.
Kumar Mukkesh et al. Diabetes research and clinical practice 2022 109237 - An early model to predict the risk of gestational diabetes mellitus in the absence of blood examination indexes: application in primary health care centres.
Wang Jingyuan et al. BMC pregnancy and childbirth 2021 21(1) 814 - Perinatal health predictors using artificial intelligence: A review.
Ramakrishnan Rema et al. Women's health (London, England) 2021 1717455065211046132 - Metabolomics can provide new insights into perinatal nutrition.
Pintus Roberta et al. Acta paediatrica (Oslo, Norway : 1992) 2021 - Prediction Method of Gestational Diabetes Based on Electronic Medical Record Data.
Liu Yang et al. Journal of healthcare engineering 2021 20216672072 - Postpartum circulating microRNA enhances prediction of future type 2 diabetes in women with previous gestational diabetes.
Joglekar Mugdha V et al. Diabetologia 2021 - Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation.
Velardo Carmelo et al. Journal of medical Internet research 2021 23(3) e21435 - Risk factors for illness severity among pregnant women with confirmed SARS-CoV-2 infection - Surveillance for Emerging Threats to Mothers and Babies Network, 20 state, local, and territorial health departments, March 29, 2020 -January 8, 2021
RR Galang et al, MEDRXIV, March 1, 2021 - Early prediction of gestational diabetes mellitus in the Chinese population via advanced machine learning.
Wu Yan-Ting et al. The Journal of clinical endocrinology and metabolism 2020 Dec - Comparison of Multivariable Logistic Regression and Other Machine Learning Algorithms for Prognostic Prediction Studies in Pregnancy Care: Systematic Review and Meta-Analysis.
Sufriyana Herdiantri et al. JMIR medical informatics 2020 Nov 8(11) e16503
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About RCH PHGKB
Reproductive and Child Health 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 reproductive and child Health...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:Oct 1, 2021
- Page last updated:May 25, 2022
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