Stroke
What's New
Last Posted: Mar 26, 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 - Emerging artificial intelligence-aided diagnosis and management methods for ischemic strokes and vascular occlusions: A comprehensive review.
G A U R I Parvathy et al. World Neurosurg X 2024 22100303 - Analyzing prehospital delays in recurrent acute ischemic stroke: Insights from interpretable machine learning.
Youli Jiang et al. Patient Educ Couns 2024 123108228 - Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data.
Jun-Bo Tu et al. Sci Rep 2024 14(1) 5245 - Developmental Prediction of Poststroke Patients in Activities of Daily Living by Using Tree-Structured Parzen Estimator-Optimized Stacking Ensemble Approaches.
Pei-Hua Lin et al. IEEE J Biomed Health Inform 2024 PP - Machine learning based predictive model of Type 2 diabetes complications using Malaysian National Diabetes Registry: A study protocol.
Mohamad Zulfikrie Abas et al. J Public Health Res 2024 13(1) 22799036241231786 - A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes.
Yongkai Liu et al. AJNR Am J Neuroradiol 2024 - Large datasets from Electronic Health Records predict seizures after ischemic strokes: A Machine Learning approach.
Alain Lekoubou et al. medRxiv 2024 - Measuring Costs of Cardiovascular Disease Prevention for Patients with Familial Hypercholesterolemia in Administrative Claims Data.
Lauren E Passero et al. High Blood Press Cardiovasc Prev 2024 - FDA Review of Radiologic AI Algorithms: Process and Challenges.
Kuan Zhang et al. Radiology 2024 310(1) e230242 - Genetics in Ischemic Stroke: Current Perspectives and Future Directions.
Ka Zhang et al. J Cardiovasc Dev Dis 2023 10(12) - Stroke classification and treatment support system artificial intelligence for usefulness of stroke diagnosis.
Nobukazu Miyamoto et al. Front Neurol 2023 141295642 - Predicting 90-day prognosis for patients with stroke: a machine learning approach.
Ahmad A Abujaber et al. Front Neurol 2023 141270767 - Detection of Cognitive Impairment From eSAGE Metadata Using Machine Learning.
Ryoma Kawakami et al. Alzheimer Dis Assoc Disord 2023 - Prediction of atrial fibrillation from at-home single-lead ECG signals without arrhythmias
M Gadaleta et al, NPJ Digital Medicine, December 12, 2023 - A clinical prediction model based on interpretable machine learning algorithms for prolonged hospital stay in acute ischemic stroke patients: a real-world study.
Kai Wang et al. Front Endocrinol (Lausanne) 2023 141165178 - Impact of CYP2C19 Genotype on Efficacy and Safety of Clopidogrel-based Antiplatelet Therapy in Stroke or Transient Ischemic Attack Patients: An Updated Systematic Review and Meta-analysis of Non-East Asian Studies.
Sarah Cargnin et al. Cardiovasc Drugs Ther 2023 - Impact of GLA Variant Classification on the Estimated Prevalence of Fabry Disease: A Systematic Review and Meta-Analysis of Screening Studies.
Emanuele Monda et al. Circ Genom Precis Med 2023 e004252 - A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model.
Giovanna Mercurio et al. Eur J Neurol 2023 - Interpretable Machine Learning-Based Predictive Modeling of Patient Outcomes Following Cardiac Surgery.
Adeel Abbasi et al. J Thorac Cardiovasc Surg 2023
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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
- Page last updated:Mar 27, 2024
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