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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

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