Angina
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Last Posted: Jan 30, 2024
- Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients.
Zihan Wang et al. Front Pharmacol 2024 141334439 - Familial risk of vasospastic angina: a nationwide family study in Sweden.
Fabrizio Ricci et al. Open Heart 2023 10(2) - Familial hypercholesterolemia is related to cardiovascular disease, heart failure and atrial fibrillation. Results from a population-based study.
Hayato Tada et al. Eur J Clin Invest 2023 e14119 - Effective Prediction of Mortality by Heart Disease Among Women in Jordan Using the Chi-Squared Automatic Interaction Detection Model: Retrospective Validation Study.
Salam Bani Hani et al. JMIR Cardio 2023 7e48795 - A novel breakthrough in wrist-worn transdermal troponin-I-sensor assessment for acute myocardial infarction.
Shantanu Sengupta et al. Eur Heart J Digit Health 2023 4(3) 145-154 - Coronary artery calcium among patients with heterozygous familial hypercholesterolaemia.
Hayato Tada et al. Eur Heart J Open 2023 3(3) oead046 - Comparison of conventional scoring systems to machine learning models for the prediction of major adverse cardiovascular events in patients undergoing coronary computed tomography angiography.
Ghorashi Seyyed Mojtaba et al. Frontiers in cardiovascular medicine 2022 9994483 - Deep learning to detect significant coronary artery disease from plain chest radiographs AI4CAD.
D'Ancona Giuseppe et al. International journal of cardiology 2022 - A machine learning-based risk warning platform for potentially inappropriate prescriptions for elderly patients with cardiovascular disease.
Xingwei Wu et al. Frontiers in pharmacology 2022 13804566 - International electronic health record-derived post-acute sequelae profiles of COVID-19 patients
HG Zhang et al, NPJ Digital Medicine, June 29, 2022 - Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study.
Lee Eunice Y et al. Environmental research 2022 113463 - Association of Lipoprotein (a) in Coronary Artery Disease in Young Individuals.
Patted Aishwarya et al. The Journal of the Association of Physicians of India 2022 70(4) 11-12 - Risk Prediction of Major Adverse Cardiovascular Events Occurrence Within 6 Months After Coronary Revascularization: Machine Learning Study.
Wang Jinwan et al. JMIR medical informatics 2022 10(4) e33395 - Impact of the ABCD-GENE Score on Clopidogrel Clinical Effectiveness after PCI: A Multi-site, Real-world Investigation.
Thomas Cameron D et al. Clinical pharmacology and therapeutics 2022 - Machine learning algorithm can provide assistance for the diagnosis of non-ST-segment elevation myocardial infarction.
Qin Lian et al. Postgraduate medical journal 2022 - Assessment of medical management in Coronary Type 2 Diabetic patients with previous percutaneous coronary intervention in Spain: A retrospective analysis of electronic health records using Natural Language Processing.
González-Juanatey Carlos et al. PloS one 2022 17(2) e0263277 - Machine learning prediction model of acute kidney injury after percutaneous coronary intervention.
Kuno Toshiki et al. Scientific reports 2022 12(1) 749 - Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine.
Sharma Abhinav et al. Diabetes care 2021 - Automatic detection of vessel structure by deep learning using intravascular ultrasound images of the coronary arteries.
Shinohara Hiroki et al. PloS one 2021 16(8) e0255577 - A new approach for interpretability and reliability in clinical risk prediction: Acute coronary syndrome scenario.
Valente Francisco et al. Artificial intelligence in medicine 2021 117102113
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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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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
- Page last updated:Apr 21, 2024
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