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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 - 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 - Predicting short-term outcomes in atrial-fibrillation-related stroke using machine learning.
Eun-Tae Jeon et al. Front Neurol 2023 141243700 - Genetic risk, adherence to healthy lifestyle and acute cardiovascular and thromboembolic complications following SARS-COV-2 infection.
Junqing Xie et al. Nat Commun 2023 14(1) 4659 - A deep learning and radiomics based Alberta stroke program early CT score method on CTA to evaluate acute ischemic stroke.
Ting Fang et al. J Xray Sci Technol 2023 - Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community.
Meraj Neyazi et al. Clin Chem Lab Med 2023 - 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 - Machine learning-based prediction of symptomatic intracerebral hemorrhage after intravenous thrombolysis for stroke: a large multicenter study.
Rui Wen et al. Front Neurol 2023 141247492 - Research participants' perception of ethical issues in stroke genomics and neurobiobanking research in Africa.
Ayodele Jegede et al. medRxiv 2023 - Genetic Variation and Sickle Cell Disease Severity: A Systematic Review and Meta-Analysis.
Justin K Kirkham et al. JAMA Netw Open 2023 6(10) e2337484 - Genetic and Nongenetic Components of Stroke Family History: A Population Study of Adopted and Nonadopted Individuals.
Ernst Mayerhofer et al. J Am Heart Assoc 2023 12(20) e031566 - Implementation of Hospital-Based Sickle Cell Newborn Screening and Follow-Up Programs in Haiti.
Ofelia A Alvarez et al. Blood Adv 2023 - Machine learning applications in stroke medicine: advancements, challenges, and future prospectives.
Mario Daidone et al. Neural Regen Res 2023 19(4) 769-773 - [Establishment and evaluation of a predictive model for early neurological deterioration after intravenous thrombolysis in acute ischemic stroke based on machine learning].
Zhe Lyu et al. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue 2023 35(9) 945-950 - Predicting Major Adverse Cardiovascular Events Following Carotid Endarterectomy Using Machine Learning.
Ben Li et al. J Am Heart Assoc 2023 e030508 - Explainable Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Machine Learning Techniques in a Population of 1780 Patients.
Chien Wei Oei et al. Sensors (Basel) 2023 23(18) - An artificial intelligence-based prognostic prediction model for hemorrhagic stroke.
Yihao Chen et al. Eur J Radiol 2023 167111081 - Combinatorial Use of Machine Learning and Logistic Regression for Predicting Carotid Plaque Risk Among 5.4 Million Adults With Fatty Liver Disease Receiving Health Check-Ups: Population-Based Cross-Sectional Study.
Yuhan Deng et al. JMIR Public Health Surveill 2023 9e47095 - Using Neural Networks Algorithm in Ischemic Stroke Diagnosis: A Systematic Review.
Suebsarn Ruksakulpiwat et al. J Multidiscip Healthc 2023 162593-2602 - Automated ASPECTS calculation may equal the performance of experienced clinicians: a machine learning study based on a large cohort.
Shu Wan et al. Eur Radiol 2023 - Development and validation of a machine learning-based prognostic risk stratification model for acute ischemic stroke.
Kai Wang et al. Sci Rep 2023 13(1) 13782 - Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation.
Jian Huang et al. Front Neurol 2023 141185447 - Cost-effectiveness analysis of implementing polygenic risk score in a workplace cardiovascular disease prevention program.
Deo Mujwara et al. Front Public Health 2023 111139496 - Comparing Explainable Machine Learning Approaches With Traditional Statistical Methods for Evaluating Stroke Risk Models: Retrospective Cohort Study.
Sermkiat Lolak et al. JMIR Cardio 2023 7e47736 - Screening for Lipid Disorders in Children and Adolescents: US Preventive Services Task Force Recommendation Statement.
et al. JAMA 2023 330(3) 253-260 - Association of Longer Leukocyte Telomere Length With Cardiac Size, Function, and Heart Failure
N Aung et al, JAMA Cardiology, July 26, 2023 - The causal effects of education on adult health, mortality and income: evidence from Mendelian randomization and the raising of the school leaving age.
Neil M Davies et al. Int J Epidemiol 2023 - Lipid Disorders in Children and Adolescents: Screening
USPSTF recommendation, July 18, 2023 - Lipoprotein(a): a Case for Universal Screening in Youth.
Aparna Alankar et al. Curr Atheroscler Rep 2023 - Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy.
Yawen Xu et al. Front Neurol 2023 141123607 - Cardiovascular disease/stroke risk stratification in deep learning framework: a review.
Mrinalini Bhagawati et al. Cardiovasc Diagn Ther 2023 13(3) 557-598 - Predicting new-onset post-stroke depression from real-world data using machine learning algorithm.
Yu-Ming Chen et al. Front Psychiatry 2023 141195586 - Using Artificial Intelligence in Predicting Ischemic Stroke Events After Percutaneous Coronary Intervention.
Chieh-Ju Chao et al. J Invasive Cardiol 2023 35(6) E297-E311 - Clinical Profiles of Children With Sickle Cell Anaemia Presenting With Acute Clinical Events: A Single-Center Study.
Anwesha Singh et al. Cureus 2023 15(5) e39008 - Development and validation of an interpretable machine learning model-Predicting mild cognitive impairment in a high-risk stroke population.
Feng-Juan Yan et al. Front Aging Neurosci 2023 151180351 - Genetic and non-genetic components of family history of stroke and heart disease: a population-based study among adopted and non-adopted individuals.
Ernst Mayerhofer et al. medRxiv 2023 - Mendelian randomization evidence for the causal effects of socio-economic inequality on human longevity among Europeans.
Chao-Jie Ye et al. Nat Hum Behav 2023 - Assessing statins use in a real-world primary care digital strategy: a cross-sectional analysis of a population-wide digital health approach
MJM Carrion et al, Lancet Regional Health, June 22, 2023 - Automatic Alberta Stroke Program Early Computed Tomographic Scoring in patients with acute ischemic stroke using diffusion-weighted imaging.
Yan Wu et al. Med Biol Eng Comput 2023 - BA.1 Bivalent COVID-19 Vaccine Use and Stroke in England.
Nick Andrews et al. JAMA 2023 6 - Study provides a more complete picture of sickle cell disease mortality burden
L Ramsey, News Medical, June 2023 - Cardiovascular disease (CVD) outcomes and associated risk factors in a medicare population without prior CVD history: an analysis using statistical and machine learning algorithms.
Gregory Yoke Hong Lip et al. Intern Emerg Med 2023 1-11 - Summary for Patients: Population Genomic Screening for Three Common Hereditary Conditions.
et al. Ann Intern Med 2023 5 (5) I19 - Social bias in artificial intelligence algorithms designed to improve cardiovascular risk assessment relative to the Framingham Risk Score: a protocol for a systematic review.
Ivneet Garcha et al. BMJ Open 2023 13(5) e067638 - Development and validation of explainable machine-learning models for carotid atherosclerosis early screening.
Ke Yun et al. J Transl Med 2023 21(1) 353 - Interpretable Machine Learning Model Predicting Early Neurological Deterioration in Ischemic Stroke Patients Treated with Mechanical Thrombectomy: A Retrospective Study.
Tongtong Yang et al. Brain Sci 2023 13(4) - Machine learning for the prediction of cognitive impairment in older adults.
Wanyue Li et al. Front Neurosci 2023 171158141 - Tumor Genomic Profile Is Associated With Arterial Thromboembolism Risk in Patients With Solid Cancer.
Stephanie Feldman et al. JACC CardioOncol 2023 5(2) 246-255 - Cardiovascular Disease Risk Assessment Using Traditional Risk Factors and Polygenic Risk Scores in the Million Veteran Program.
Jason L Vassy et al. JAMA Cardiol 2023 5 - Thrombophilia screening in the routine clinical care of children with arterial ischemic stroke.
Kristin Maher et al. Pediatr Blood Cancer 2023 e30381 - Artificial neural network machine learning prediction of the smoking behavior and health risks perception of Indonesian health professionals.
Desy Nuryunarsih et al. Environ Anal Health Toxicol 2023 38(1) e2023003-0 - A Hybrid Stacked CNN and Residual Feedback GMDH-LSTM Deep Learning Model for Stroke Prediction Applied on Mobile AI Smart Hospital Platform.
Bassant M Elbagoury et al. Sensors (Basel) 2023 23(7) - A machine learning model for visualization and dynamic clinical prediction of stroke recurrence in acute ischemic stroke patients: A real-world retrospective study.
Kai Wang et al. Front Neurosci 2023 171130831 - Defining the Age of Young Ischemic Stroke Using Data-Driven Approaches.
Vida Abedi et al. J Clin Med 2023 12(7) - Prediction of blood pressure variability during thrombectomy using supervised machine learning and outcomes of patients with ischemic stroke from large vessel occlusion.
Daniel Najafali et al. J Thromb Thrombolysis 2023 - Stroke, Myocardial Infarction, and Pulmonary Embolism after Bivalent Booster.
Marie-Joelle Jabagi et al. N Engl J Med 2023 3 (15) 1431-1432 - Genetic Susceptibility to Mood Disorders and Risk of Stroke: A Polygenic Risk Score and Mendelian Randomization Study.
Jiangming Sun et al. Stroke 2023 - Using Deep-Learning-Based Artificial Intelligence Technique to Automatically Evaluate the Collateral Status of Multiphase CTA in Acute Ischemic Stroke.
Chun-Chao Huang et al. Tomography (Ann Arbor, Mich.) 2023 9(2) 647-656 - Development and validation of machine learning-based model for mortality prediction in patients with acute basilar artery occlusion receiving endovascular treatment: multicentric cohort analysis.
Chang Liu et al. Journal of neurointerventional surgery 2023 - Assessing the performance of genetic risk score for stratifying risk of post-sepsis cardiovascular complications.
Brian McElligott et al. Frontiers in cardiovascular medicine 2023 101076745 - Impact of Genetic polymorphisms on the risk of epilepsy amongst patients with acute brain injury: a systematic review.
Shubham Misra et al. European journal of neurology 2023 - Predicting Pain in People With Sickle Cell Disease in the Day Hospital Using the Commercial Wearable Apple Watch: Feasibility Study.
Rebecca Sofia Stojancic et al. JMIR formative research 2023 7e45355 - The predictors of death within 1 year in acute ischemic stroke patients based on machine learning.
Kai Wang et al. Frontiers in neurology 2023 141092534 - Big Data in Stroke: How to Use Big Data to Make the Next Management Decision.
Yuzhe Liu et al. Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics 2023 - MRI Radiomics and Predictive Models in Assessing Ischemic Stroke Outcome-A Systematic Review.
Hanna Maria Drago? et al. Diagnostics (Basel, Switzerland) 2023 13(5) - Keeping Quiet About Genetic Risk.
Susanna J Smith et al. Health affairs (Project Hope) 2023 3 (3) 443-447 - ASOC Osuntokun Award Lecture 2022: Partnership for stroke prevention and treatment in Africa: Qualitative research processes and findings.
Carolyn Jenkins et al. Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 2023 107060 - Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.
Michael Dieckmeyer et al. Clinical neuroradiology 2023 - Genetic variation supports a causal role for valproate in prevention of ischemic stroke.
Ernst Mayerhofer et al. medRxiv : the preprint server for health sciences 2023 - Development and validation of echocardiography-based machine-learning models to predict mortality.
Akshay Valsaraj et al. EBioMedicine 2023 90104479 - Development of rapid and effective risk prediction models for stroke in the Chinese population: a cross-sectional study.
Yuexin Qiu et al. BMJ open 2023 13(3) e068045 - The artificial sweetener erythritol and cardiovascular event risk.
Marco Witkowski et al. Nature medicine 2023 2 - Development and Validation of a Novel Score for Predicting Long-Term Mortality after an Acute Ischemic Stroke.
Ching-Heng Lin et al. International journal of environmental research and public health 2023 20(4) - Value of baseline characteristics in the risk prediction of atrial fibrillation.
Jiacheng He et al. Frontiers in cardiovascular medicine 2023 101068562 - Life's Essential 8 and 10-Year and Lifetime Risk of Atherosclerotic Cardiovascular Disease in China.
Cheng Jin et al. American journal of preventive medicine 2023 - Predicting later categories of upper limb activity from earlier clinical assessments following stroke: an exploratory analysis.
Jessica Barth et al. Journal of neuroengineering and rehabilitation 2023 20(1) 24 - Social Determinants, Cardiovascular Disease, and Health Care Cost: A Nationwide Study in the United States Using Machine Learning.
Feinuo Sun et al. Journal of the American Heart Association 2023 e027919 - Stroke mortality prediction based on ensemble learning and the combination of structured and textual data.
Ruixuan Huang et al. Computers in biology and medicine 2023 155106176 - A Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage.
Evangelos Pavlos Myserlis et al. Stroke 2023 - Association of Hypertensive Disorders of Pregnancy With Future Cardiovascular Disease.
Bilal Rayes et al. JAMA network open 2023 2 (2) e230034 - Development and validation of ischemic heart disease and stroke prognostic models using large-scale real-world data from Japan.
Shigeto Yoshida et al. Environmental health and preventive medicine 2023 2816 - Ischemic stroke after COVID-19 bivalent vaccine administration in patients aged 65 years and older: analysis of nation-wide patient electronic health records in the United States
M Gorenflo et al, MEDRXIV, February 14, 2023 - Efficacy and safety of pharmacological interventions for managing sickle cell disease in children and adolescents: protocol for a systematic review with network meta-analysis.
Fernanda S Tonin et al. BMJ open 2023 13(2) e064872 - Genetic Risk Score Improves Risk Stratification for Anticoagulation-Related Intracerebral Hemorrhage.
Ernst Mayerhofer et al. Stroke 2023 - Evaluation of Blood Biomarkers and Parameters for the Prediction of Stroke Survivors' Functional Outcome upon Discharge Utilizing Explainable Machine Learning.
Aimilios Gkantzios et al. Diagnostics (Basel, Switzerland) 2023 13(3) - Integrated Machine Learning Decision Tree Model for Risk Evaluation in Patients with Non-Valvular Atrial Fibrillation When Taking Different Doses of Dabigatran.
Yung-Chuan Huang et al. International journal of environmental research and public health 2023 20(3) - Prediction of short-term atrial fibrillation risk using primary care electronic health records.
Ramesh Nadarajah et al. Heart (British Cardiac Society) 2023 - The diagnostic performance of artificial intelligence algorithms for identifying M2 segment middle cerebral artery occlusions: A systematic review and meta-analysis.
Sherief Ghozy et al. Journal of neuroradiology = Journal de neuroradiologie 2023 - Factors Associated with Stroke after COVID-19 Vaccination: A Statewide Analysis
F Nahab et al, MEDRXIV, February 9, 2023 - Twenty-eight-day in-hospital mortality prediction for elderly patients with ischemic stroke in the intensive care unit: Interpretable machine learning models.
Jian Huang et al. Frontiers in public health 2023 101086339 - Validation of risk prediction models applied to longitudinal electronic health record data for the prediction of major cardiovascular events in the presence of data shifts.
Yikuan Li et al. European heart journal. Digital health 2023 3(4) 535-547 - Rupture discrimination of multiple small (< 7 mm) intracranial aneurysms based on machine learning-based cluster analysis.
Xin Tong et al. BMC neurology 2023 23(1) 45 - Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.
Artem Zatcepin et al. Zeitschrift fur medizinische Physik 2023 - Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups.
Chuan Hong et al. JAMA 2023 329(4) 306-317 - Prevalence of Diabetes and Its Association with Atherosclerotic Cardiovascular Disease Risk in Patients with Familial Hypercholesterolemia: An Analysis from the Hellenic Familial Hypercholesterolemia Registry (HELLAS-FH).
Boutari Chrysoula et al. Pharmaceuticals (Basel, Switzerland) 2023 16(1) - Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction.
Miyazawa Kazuo et al. Nature genetics 2023 - Imaging and Hemodynamic Characteristics of Vulnerable Carotid Plaques and Artificial Intelligence Applications in Plaque Classification and Segmentation.
Han Na et al. Brain sciences 2023 13(1) - Stroke prevention in rural residents: development of a simplified risk assessment tool with artificial intelligence.
Ding Zhongao et al. Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology 2023 - Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population.
Orii Makoto et al. The international journal of cardiovascular imaging 2023 - Are there differences in perceptions, preferences and attitudes towards disclosure of genetic testing for Stroke? A qualitative study among stroke-free SIREN-SIBS genomics study participants.
Arulogun Oyedunni et al. Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 2023 32(3) 106978 - Use of Family History of cardiovascular disease or chronic hypertension to better identify who needs postpartum cardiovascular risk screening.
Ackerman-Banks Christina M et al. American journal of obstetrics & gynecology MFM 2023 100850 - Sickle Cell Cure Brings Mix of Anxiety and Hope
G Kolata, NY Times, January 17, 2023 - Deep learning for collateral evaluation in ischemic stroke with imbalanced data.
Aktar Mumu et al. International journal of computer assisted radiology and surgery 2023 - Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke.
Amann Julia et al. PloS one 2023 18(1) e0279088 - Prediction of type 2 diabetes mellitus using hematological factors based on machine learning approaches: a cohort study analysis.
Mansoori Amin et al. Scientific reports 2023 13(1) 663 - CDC & FDA Identify Preliminary COVID-19 Vaccine Safety Signal for Persons Aged 65 Years and Older
CDC, January 13, 2023 - Advanced Hemodynamic Monitoring Allows Recognition of Early Response Patterns to Diuresis in Congestive Heart Failure Patients.
Dagan Maya et al. Journal of clinical medicine 2023 12(1) - Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention.
Marston Nicholas A et al. JAMA cardiology 2022 - Qualitative and quantitative effects of PCSK9 inhibitors in familial hypercholesterolemia: a synthetic review.
Shakir Aamina et al. Current problems in cardiology 2022 101550 - Systolic Blood Pressure and Cardiovascular Risk in Patients With Diabetes: A Prospective Cohort Study.
Rao Shishir et al. Hypertension (Dallas, Tex. : 1979) 2022 - Assessing electrocardiogram changes after ischemic stroke with artificial intelligence.
Zeng Ziqiang et al. PloS one 2022 17(12) e0279706 - Answering Clinical Questions Using Machine Learning: Should We Look at Diastolic Blood Pressure When Tailoring Blood Pressure Control?
Sinski Maciej et al. Journal of clinical medicine 2022 11(24) - Development and Validation of Machine Learning Models to Classify Artery Stenosis for Automated Generating Ultrasound Report.
Yeh Chih-Yang et al. Diagnostics (Basel, Switzerland) 2022 12(12) - Prediction of Hemorrhagic Complication after Thrombolytic Therapy Based on Multimodal Data from Multiple Centers: An Approach to Machine Learning and System Implementation.
Cui Shaoguo et al. Journal of personalized medicine 2022 12(12) - Genetic Causes of Cerebral Small Vessel Diseases: A Practical Guide for Neurologists.
Manini Arianna et al. Neurology 2022 - Artificial intelligence-driven ASPECTS for the detection of early stroke changes in non-contrast CT: a systematic review and meta-analysis.
Adamou Antonis et al. Journal of neurointerventional surgery 2022 - Personalized prediction of incident hospitalization for cardiovascular disease in patients with hypertension using machine learning.
Feng Yuanchao et al. BMC medical research methodology 2022 22(1) 325 - Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study.
Liu Jia et al. European radiology 2022 - Prediction of incident cardiovascular events using machine learning and CMR radiomics.
Pujadas Esmeralda Ruiz et al. European radiology 2022 - Deep transformation models for functional outcome prediction after acute ischemic stroke.
Herzog Lisa et al. Biometrical journal. Biometrische Zeitschrift 2022 - An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke risk.
Raghunath Sushravya et al. Journal of electrocardiology 2022 7661-65 - An explainable machine learning model for predicting the outcome of ischemic stroke after mechanical thrombectomy.
Yao Zhelv et al. Journal of neurointerventional surgery 2022 - Experience, Knowledge, and Perceptions of Pharmacogenomics among Pharmacists and Nurse Practitioners in Alberta Hospitals.
Hayashi Meagan et al. Pharmacy (Basel, Switzerland) 2022 10(6) - A Catalogue of Machine Learning Algorithms for Healthcare Risk Predictions.
Mavrogiorgou Argyro et al. Sensors (Basel, Switzerland) 2022 22(22) - An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation.
Moghadam Saeed Montazeri et al. The Lancet. Digital health 2022 4(12) e884-e892 - Classification of Blood Pressure Levels Based on Photoplethysmogram and Electrocardiogram Signals with a Concatenated Convolutional Neural Network.
Fuadah Yunendah Nur et al. Diagnostics (Basel, Switzerland) 2022 12(11) - Deep Learning in Ischemic Stroke Imaging Analysis: A Comprehensive Review.
Cui Liyuan et al. BioMed research international 2022 20222456550 - Word2vec Word Embedding-Based Artificial Intelligence Model in the Triage of Patients with Suspected Diagnosis of Major Ischemic Stroke: A Feasibility Study.
Desai Antonio et al. International journal of environmental research and public health 2022 19(22) - The Utility of Automated ASPECTS in Acute Ischemic Stroke for Intravenous Recombinant Tissue Plasminogen Activator (IV-rtPA) Therapy.
Shibata Soichiro et al. Neurology international 2022 14(4) 981-990 - Substantially Elevated Atherosclerotic Risks in Japanese Severe Familial Hypercholesterolemia Defined by the International Atherosclerosis Society.
Funabashi Sayaka et al. JACC. Asia 2022 1(2) 245-255 - eXplainable AI allows predicting upper limb rehabilitation outcomes in sub-acute stroke patients.
Marialuisa Gandolfi et al. IEEE journal of biomedical and health informatics 2022 PP - Pharmacogenomics in Stroke and Cardiovascular Disease: State of the Art.
Ross Stephanie et al. Stroke 2022 - AI-driven Stroke Rehabilitation Systems and Assessment: A Systematic Review.
Rahman Sejuti et al. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society 2022 PP - Multi-modal fusion model for predicting adverse cardiovascular outcome post percutaneous coronary intervention.
Bhattacharya Amartya et al. Physiological measurement 2022 - 5 Things You Should Know About Epilepsy
CDC, November 2022 - Application of Machine Learning Techniques for Characterization of Ischemic Stroke with MRI Images: A Review.
Subudhi Asit et al. Diagnostics (Basel, Switzerland) 2022 12(10) - Automatic identification of early ischemic lesions on non-contrast CT with deep learning approach.
Sahoo Prasan Kumar et al. Scientific reports 2022 12(1) 18054 - Individualising intensive systolic blood pressure reduction in hypertension using computational trial phenomaps and machine learning: a post-hoc analysis of randomised clinical trials.
Oikonomou Evangelos K et al. The Lancet. Digital health 2022 4(11) e796-e805 - Predictors of Adherence to Stroke Prevention in the BALKAN-AF Study: A Machine-Learning Approach.
Koziel-Siolkowska Monika et al. TH open : companion journal to thrombosis and haemostasis 2022 6(3) e283-e290 - Rapid lipid-laden plaque identification in intravascular optical coherence tomography imaging based on time-series deep learning.
Rico-Jimenez Jose J et al. Journal of biomedical optics 2022 27(10) - Wearable Sensors Improve Prediction of Post-Stroke Walking Function Following Inpatient Rehabilitation.
O'Brien Megan K et al. IEEE journal of translational engineering in health and medicine 2022 102100711 - Prediction of atrial fibrillation and stroke using machine learning models in UK Biobank.
A Papadopolou et al, MEDRXIV, October 30, 2022 - Association of Vascular Risk Factors and Genetic Factors With Penetrance of Variants Causing Monogenic Stroke.
Cho Bernard P H et al. JAMA neurology 2022 10 - Monogenic Stroke-Can We Overcome Nature With Nurture?
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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.
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