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) - Genetic testing in cardiovascular disease.
Michael P Gray et al. Med J Aust 2024 - Integration of a polygenic score into guideline-recommended prediction of cardiovascular disease.
Ling Li et al. Eur Heart J 2024 - Physical signs and atherosclerotic cardiovascular disease in familial hypercholesterolemia: the HELLAS-FH Registry.
Loukianos S Rallidis et al. J Cardiovasc Med (Hagerstown) 2024 - Analyzing prehospital delays in recurrent acute ischemic stroke: Insights from interpretable machine learning.
Youli Jiang et al. Patient Educ Couns 2024 123108228 - Coronary artery disease evaluation during transcatheter aortic valve replacement work-up using photon-counting CT and artificial intelligence.
Jan M Brendel et al. Diagn Interv Imaging 2024 - International Atherosclerosis Society Roadmap for Familial Hypercholesterolaemia.
Gerald F Watts et al. Glob Heart 2024 19(1) 12 - Artificial Intelligence in Coronary Artery Calcium Scoring Detection and Quantification.
Khaled Abdelrahman et al. Diagnostics (Basel) 2024 14(2) - Dose-Response Associations of Lipid Traits With Coronary Artery Disease and Mortality.
Guoyi Yang et al. JAMA Netw Open 2024 1 (1) e2352572 - Clinical and genetic diagnosis of familial hypercholesterolaemia in patients undergoing coronary angiography: the Ludwigshafen Risk and Cardiovascular Health Study.
Stefan Molnar et al. Eur Heart J Qual Care Clin Outcomes 2024 - Machine Learning for Early Prediction of Major Adverse Cardiovascular Events After First Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Retrospective Cohort Study.
Pin Zhang et al. JMIR Form Res 2024 8e48487 - Effect of Comorbidities Features in Machine Learning Models for Survival Analysis to Predict Prodromal Alzheimer's Disease.
Ferial Abuhantash et al. Annu Int Conf IEEE Eng Med Biol Soc 2023 20231-4 - Identification and risk stratification of coronary disease by artificial intelligence-enabled ECG.
Samir Awasthi et al. EClinicalMedicine 2023 65102259 - Family history, socioeconomic factors, comorbidities, health behaviors, and the risk of sudden cardiac arrest.
Eujene Jung et al. Sci Rep 2023 13(1) 21341 - Dynamic Importance of Genomic and Clinical Risk for Coronary Artery Disease Over the Life Course.
Sarah M Urbut et al. medRxiv 2023 - Genetic risk, adherence to healthy lifestyle and acute cardiovascular and thromboembolic complications following SARS-COV-2 infection.
Junqing Xie et al. Nat Commun 2023 14(1) 4659 - Machine Learning in Cardiovascular Risk Prediction and Precision Preventive Approaches.
Nitesh Gautam et al. Curr Atheroscler Rep 2023 - Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT.
Hee Sang Oh et al. Eur Radiol 2023 - The GenoVA study: Equitable implementation of a pragmatic randomized trial of polygenic-risk scoring in primary care.
Jason L Vassy et al. Am J Hum Genet 2023 110(11) 1841-1852 - Association Between a First-Degree Family History and Self-Reported Personal History of Obesity, Diabetes, and Heart and Blood Conditions: Results From the All of Us Research Program.
Danielle Rasooly et al. J Am Heart Assoc 2023 11 e030779 - Ancestry-specific polygenic risk scores are risk enhancers for clinical cardiovascular disease assessments.
George B Busby et al. Nat Commun 2023 11 (1) 7105 - Novel Finnish-enriched variants causing severe hypercholesterolemia and their clinical impact on coronary artery disease.
Nella Junna et al. Atherosclerosis 2023 117327 - Predictive capacity of a genetic risk score for coronary artery disease in assessing recurrences and cardiovascular mortality among patients with myocardial infarction.
Luis Miguel Rincón et al. Front Cardiovasc Med 2023 101254066 - Artificial intelligence evaluation of coronary computed tomography angiography for coronary stenosis classification and diagnosis.
Dan-Ying Lee et al. Eur J Clin Invest 2023 e14089 - Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study.
Mehdi Amini et al. Sci Rep 2023 13(1) 14920 - Machine learning models in predicting health care costs in patients with a recent acute coronary syndrome: A prospective pilot study.
Arto J Hautala et al. Cardiovasc Digit Health J 2023 4(4) 137-142 - Cardiac Failure Forecasting Based on Clinical Data Using a Lightweight Machine Learning Metamodel.
Istiak Mahmud et al. Diagnostics (Basel) 2023 13(15) - Automatic extraction of coronary arteries using deep learning in invasive coronary angiograms.
Yinghui Meng et al. Technol Health Care 2023 - Cost-effectiveness analysis of implementing polygenic risk score in a workplace cardiovascular disease prevention program.
Deo Mujwara et al. Front Public Health 2023 111139496 - Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries.
Bernhard Föllmer et al. Nat Rev Cardiol 2023 7 - Application of genetic risk score for in-stent restenosis of second- and third-generation drug-eluting stents in geriatric patients.
Yu-Ling Hsu et al. BMC Geriatr 2023 23(1) 443
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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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