Coronary Artery Disease
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Last Posted: Jun 19, 2024
- Machine learning models for assessing risk factors affecting health care costs: 12-month exercise-based cardiac rehabilitation.
Arto J Hautala et al. Front Public Health 2024 121378349 - MSGene: a multistate model using genetic risk and the electronic health record applied to lifetime risk of coronary artery disease.
Sarah M Urbut et al. Nat Commun 2024 15(1) 4884 - Enhancing Prediction of Myocardial Recovery After Coronary Revascularization: Integrating Radiomics from Myocardial Contrast Echocardiography with Machine Learning.
Deyi Huang et al. Int J Gen Med 2024 172539-2555 - Exceptional Genetics, Generalizable Therapeutics, and Coronary Artery Disease
- Influence of Polygenic Background on the Clinical Presentation of Familial Hypercholesterolemia.
Mark Trinder et al. Arterioscler Thromb Vasc Biol 2024 - Development, evaluation and validation of machine learning models to predict hospitalizations of patients with coronary artery disease within the next 12 months.
Andrey D Ermak et al. Int J Med Inform 2024 188105476 - Algorithm for detection and screening of familial hypercholesterolemia in Lithuanian population.
Urte Aliosaitiene et al. Lipids Health Dis 2024 23(1) 136 - Enhanced identification of familial hypercholesterolemia using central laboratory algorithms.
Shirin Ibrahim et al. Atherosclerosis 2024 393117548 - Modification of coronary artery disease clinical risk factors by coronary artery disease polygenic risk score.
Buu Truong et al. Med 2024 - Development of a Non-Invasive Machine-Learned Point-of-Care Rule-Out Test for Coronary Artery Disease.
Timothy Burton et al. Diagnostics (Basel) 2024 14(7)
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About HLBS-PopOmics
HLBS-PopOmics 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 Heart and Vascular Diseases(H), Lung Diseases(L), Blood Diseases(B), and Sleep Disorders(S)...more
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Site Citation:
Mensah GA, Yu W, Barfield WL, Clyne M, Engelgau MM, Khoury MJ. HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders. Genet Med. 2018 Sep 10. doi: 10.1038/s41436-018-0118-1
Disclaimer: Articles listed in the Public Health Knowledge Base are selected by Public Health Genomics Branch 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, 2024
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