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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Last data update: May 03, 2024
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Development of a Non-Invasive Machine-Learned Point-of-Care Rule-Out Test for Coronary Artery Disease.
Timothy Burton et al. Diagnostics (Basel) 2024 14(7)
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Analyzing prehospital delays in recurrent acute ischemic stroke: Insights from interpretable machine learning.
Youli Jiang et al. Patient Educ Couns 2024 123108228
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Coronary artery disease evaluation during transcatheter aortic valve replacement work-up using photon-counting CT and artificial intelligence.
Jan M Brendel et al. Diagn Interv Imaging 2024
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Artificial Intelligence in Coronary Artery Calcium Scoring Detection and Quantification.
Khaled Abdelrahman et al. Diagnostics (Basel) 2024 14(2)
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Machine Learning for Early Prediction of Major Adverse Cardiovascular Events After First Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Retrospective Cohort Study.
Pin Zhang et al. JMIR Form Res 2024 8e48487
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Effect of Comorbidities Features in Machine Learning Models for Survival Analysis to Predict Prodromal Alzheimer's Disease.
Ferial Abuhantash et al. Annu Int Conf IEEE Eng Med Biol Soc 2023 20231-4
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Identification and risk stratification of coronary disease by artificial intelligence-enabled ECG.
Samir Awasthi et al. EClinicalMedicine 2023 65102259
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Machine Learning in Cardiovascular Risk Prediction and Precision Preventive Approaches.
Nitesh Gautam et al. Curr Atheroscler Rep 2023
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Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT.
Hee Sang Oh et al. Eur Radiol 2023
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Artificial intelligence evaluation of coronary computed tomography angiography for coronary stenosis classification and diagnosis.
Dan-Ying Lee et al. Eur J Clin Invest 2023 e14089
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Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study.
Mehdi Amini et al. Sci Rep 2023 13(1) 14920
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Machine learning models in predicting health care costs in patients with a recent acute coronary syndrome: A prospective pilot study.
Arto J Hautala et al. Cardiovasc Digit Health J 2023 4(4) 137-142
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Cardiac Failure Forecasting Based on Clinical Data Using a Lightweight Machine Learning Metamodel.
Istiak Mahmud et al. Diagnostics (Basel) 2023 13(15)
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Automatic extraction of coronary arteries using deep learning in invasive coronary angiograms.
Yinghui Meng et al. Technol Health Care 2023
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Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries.
Bernhard Föllmer et al. Nat Rev Cardiol 2023
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Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images.
Tareen Dawood et al. Med Image Anal 2023 88102861
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Validation of the commercial coronary computed tomographic angiography artificial intelligence for coronary artery stenosis: a cross-sectional study.
Qi Han et al. Quant Imaging Med Surg 2023 13(6) 3789-3801
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Revolutionizing healthcare: artificial intelligence detection of coronary artery disease paves the way for future tools.
Mauro Massussi et al. J Cardiovasc Med (Hagerstown) 2023 24(7) 467-468
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Electrocardiogram-based deep learning algorithm for the screening of obstructive coronary artery disease.
Seong Huan Choi et al. BMC Cardiovasc Disord 2023 23(1) 287
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Can machine learning unravel unsuspected, clinically important factors predictive of long-term mortality in complex coronary artery disease? A call for 'big data'.
Kai Ninomiya et al. Eur Heart J Digit Health 2023 4(3) 275-278
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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
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Pre-test probability for coronary artery disease in patients with chest pain based on machine learning techniques.
Byoung Geol Choi et al. Int J Cardiol 2023
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Machine learning-enhanced echocardiography for screening coronary artery disease.
Ying Guo et al. Biomed Eng Online 2023 22(1) 44
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The feasibility of early detecting coronary artery disease using deep learning-based algorithm based on electrocardiography.
Panli Tang et al. Aging (Albany NY) 2023 15(9) 3524-3537
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A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease.
Valeria Raparelli et al. Clinical research in cardiology : official journal of the German Cardiac Society 2023
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SERS spectroscopy with machine learning to analyze human plasma derived sEVs for coronary artery disease diagnosis and prognosis.
Xi Huang et al. Bioengineering & translational medicine 2023 8(2) e10420
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Artificial intelligence in coronary computed tomography angiography: Demands and solutions from a clinical perspective.
Bettina Baeßler et al. Frontiers in cardiovascular medicine 2023 101120361
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Deep learning applications in coronary anatomy imaging: a systematic review and meta-analysis.
Ebraham Alskaf et al. Journal of medical artificial intelligence 2023 511
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Performance of machine learning-based coronary computed tomography angiography for selecting revascularization candidates.
Zengfa Huang et al. Acta radiologica (Stockholm, Sweden : 1987) 2023 2841851231158730
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Determinants of implementing artificial intelligence-based clinical decision support tools in healthcare: a scoping review protocol.
Bishnu Bajgain et al. BMJ open 2023 13(2) e068373
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Page last reviewed:
Feb 1, 2024
Page last updated:
May 03, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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