Stroke
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Last Posted: Jun 20, 2024
- CYP2C19 Genotype Is Associated With Adverse Cardiovascular Outcomes in Black Patients Treated With Clopidogrel Undergoing Percutaneous Coronary Intervention.
Kayla R Tunehag et al. J Am Heart Assoc 2024 e033791 - Systematic Review and Meta-Analysis of Prehospital Machine Learning Scores as Screening Tools for Early Detection of Large Vessel Occlusion in Patients With Suspected Stroke.
Muath Alobaida et al. J Am Heart Assoc 2024 e033298 - Polygenic risk score adds to a clinical risk score in the prediction of cardiovascular disease in a clinical setting.
Nilesh J Samani et al. Eur Heart J 2024 - A novel higher performance nomogram based on explainable machine learning for predicting mortality risk in stroke patients within 30 days based on clinical features on the first day ICU admission.
Haoran Chen et al. BMC Med Inform Decis Mak 2024 24(1) 161 - Deep Learning-Based Automatic Classification of Ischemic Stroke Subtype Using Diffusion-Weighted Images.
Wi-Sun Ryu et al. J Stroke 2024 26(2) 300-311 - The potential of virtual triage AI to improve early detection, care acuity alignment, and emergent care referral of life-threatening conditions.
George A Gellert et al. Front Public Health 2024 121362246 - 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) - Cardiovascular outcomes in patients with homozygous familial hypercholesterolaemia on lipoprotein apheresis initiated during childhood: long-term follow-up of an international cohort from two registries.
M Doortje Reijman et al. Lancet Child Adolesc Health 2024 - StrokeClassifier: ischemic stroke etiology classification by ensemble consensus modeling using electronic health records.
Ho-Joon Lee et al. NPJ Digit Med 2024 7(1) 130 - Developing machine learning models to predict multi-class functional outcomes and death three months after stroke in Sweden.
Josline Adhiambo Otieno et al. PLoS One 2024 19(5) e0303287 - Utilizing machine learning to facilitate the early diagnosis of posterior circulation stroke.
Ahmad A Abujaber et al. BMC Neurol 2024 24(1) 156 - Identifying dementia from cognitive footprints in hospital records among Chinese older adults: a machine-learning study.
Jiayi Zhou et al. Lancet Reg Health West Pac 2024 46101060 - Many Models, Little Adoption-What Accounts for Low Uptake of Machine Learning Models for Atrial Fibrillation Prediction and Detection?
Yuki Kawamura et al. J Clin Med 2024 13(5) - Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study.
Richard M Yoo et al. JMIR Med Inform 2024 12e51171 - Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing.
Marta Fernandes et al. medRxiv 2024 - Machine Learning-Based Prediction of Stroke in Emergency Departments.
Vida Abedi et al. Ther Adv Neurol Disord 2024 1717562864241239108 - Integration of a polygenic score into guideline-recommended prediction of cardiovascular disease.
Ling Li et al. Eur Heart J 2024 - PRERISK: A Personalized, Artificial Intelligence-Based and Statistically-Based Stroke Recurrence Predictor for Recurrent Stroke.
Giorgio Colangelo et al. Stroke 2024 - Physical signs and atherosclerotic cardiovascular disease in familial hypercholesterolemia: the HELLAS-FH Registry.
Loukianos S Rallidis et al. J Cardiovasc Med (Hagerstown) 2024 - Development and Validation of Machine Learning Algorithms to Predict 1-Year Ischemic Stroke and Bleeding Events in Patients with Atrial Fibrillation and Cancer.
Bang Truong et al. Cardiovasc Toxicol 2024
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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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