Last Posted: Mar 20, 2023
- Role of artificial intelligence and machine learning in interventional cardiology.
Shoaib Subhan et al. Current problems in cardiology 2023 101698
- Generalizable and robust deep learning algorithm for atrial fibrillation diagnosis across geography, ages and sexes.
Shany Biton et al. NPJ digital medicine 2023 3 (1) 44
- An artificial intelligence-based model for prediction of atrial fibrillation from single-lead sinus rhythm electrocardiograms facilitating screening.
Tove Hygrell et al. Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology 2023
- Sudden cardiac death in the young: An update for NPs.
Julianne Doucette et al. The Nurse practitioner 2023 48(3) 21-28
- Value of baseline characteristics in the risk prediction of atrial fibrillation.
Jiacheng He et al. Frontiers in cardiovascular medicine 2023 101068562
- A novel artificial intelligence based algorithm to reduce wearable cardioverter-defibrillator alarms.
Jeffrey Arkles et al. Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing 2023
- Multi-center retrospective cohort study applying deep learning to electrocardiograms to identify left heart valvular dysfunction
A Vaid et al, Comm Med, February 14, 2023
- Machine learning of electrophysiological signals for the prediction of ventricular arrhythmias: systematic review and examination of heterogeneity between studies.
Maarten Z H Kolk et al. EBioMedicine 2023 89104462
- Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms.
Weijie Sun et al. NPJ digital medicine 2023 6(1) 21
- An intelligent health monitoring and diagnosis system based on the internet of things and fuzzy logic for cardiac arrhythmia COVID-19 patients.
Muhammad Zia Rahman et al. Computers in biology and medicine 2023 154106583
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 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.
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- Page last updated:Mar 21, 2023
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