Last Posted: Apr 04, 2023
- Identification of Recurrent Atrial Fibrillation using Natural Language Processing Applied to Electronic Health Records.
Chengyi Zheng et al. European heart journal. Quality of care & clinical outcomes 2023
- Genotype-phenotype associations in atrial fibrillation: meta-analysis.
Hu Zhen, et al. Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing 2018 0 (3) 283-288
- Catheter ablation for monomorphic ventricular tachycardia in Brugada syndrome patients: detailed characteristics and long-term follow-up.
Tokioka Sayuri, et al. Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing 2019 0 (1) 97-103
- A Higher Polygenic Risk Score Is Associated with a Higher Recurrence Rate of Atrial Fibrillation in Direct Current Cardioversion-Treated Patients.
Vogel Simon, et al. Medicina (Kaunas, Lithuania) 2021 0 (11)
- sST2 and Galectin-3 genotyping in patients with persistent atrial fibrillation.
Saez-Maleta Ruth, et al. Molecular biology reports 2021 0 (2) 1601-1606
- Qualitative Evaluation of an Artificial Intelligence-Based Clinical Decision Support System to Guide Rhythm Management of Atrial Fibrillation: Survey Study.
Stacy John et al. JMIR formative research 2022 6(8) e36443
- Mobile health technology in atrial fibrillation.
Bonini Niccolò et al. Expert review of medical devices 2022 1-14
- Identification of Incident Atrial Fibrillation From Electronic Medical Records.
Chamberlain Alanna M et al. Journal of the American Heart Association 2022 e023237
- Atrial fibrillation in older patients and artificial intelligence: a quantitative demonstration of a link with some of the geriatric multidimensional assessment tools-a preliminary report.
Fumagalli Stefano et al. Aging clinical and experimental research 2020 Oct
- Role for machine learning in sex-specific prediction of successful electrical cardioversion in atrial fibrillation?
Vinter Nicklas et al. Open heart 2020 Jun 7(1)
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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