Echocardiography
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Last Posted: Jun 25, 2024
- A machine learning-derived risk score to predict left ventricular diastolic dysfunction from clinical cardiovascular magnetic resonance imaging.
Qingtao Zhou et al. Front Cardiovasc Med 2024 111382418 - Deep Learning for Echo Analysis, Tracking, and Evaluation of Mitral Regurgitation (DELINEATE-MR).
Aaron Long et al. Circulation 2024 - 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 - Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients.
Chua Ming et al. J Pers Med 2024 14(5) - Artificial Intelligence Assessment of Biological Age from Transthoracic Echocardiography: Discrepancies to Chronologic Age Predict Significant Excess Mortality.
Kobi Faierstein et al. J Am Soc Echocardiogr 2024 - Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases.
Yu-Ting Lin et al. Aging (Albany NY) 2024 16 - The use of artificial intelligence for predicting postinfarction myocardial viability in echocardiographic images.
Blazej Michalski et al. Cardiol J 2024 - Clinical Interpretation of Genetic Variants in the Evaluation and Management of Thoracic Aortic Aneurysm and Dissection.
Zaid Abood et al. Am J Med 2024 - Echocardiographic Detection of Regional Wall Motion Abnormalities using Artificial Intelligence Compared to Human Readers.
Jeremy A Slivnick et al. J Am Soc Echocardiogr 2024 - Explainable machine learning using echocardiography to improve risk prediction in patients with chronic coronary syndrome.
Mitchel A Molenaar et al. Eur Heart J Digit Health 2024 5(2) 170-182
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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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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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