AIMC Topic: Coronary Artery Disease

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Machine Learning Outperforms ACC / AHA CVD Risk Calculator in MESA.

Journal of the American Heart Association Nov 20, 2018
Background Studies have demonstrated that the current US guidelines based on American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equations Risk Calculator may underestimate risk of atherosclerotic cardiovascular disease ...
Humans Machine Learning Female Risk Factors Middle Aged Risk Assessment Support Vector Machine Coronary Artery Disease Hydroxymethylglutaryl-CoA Reductase Inhibitors Aged Sensitivity and Specificity Male Cardiovascular Diseases
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Multiobjective multifactor dimensionality reduction to detect SNP-SNP interactions.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: Single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) are popular markers for understanding disease susceptibility. Multifactor dimensionality reduction (MDR) can successfully detect considerable SSIs. Currently, MDR-based methods ...
Models, Genetic Coronary Artery Disease Epistasis, Genetic Multifactor Dimensionality Reduction Case-Control Studies Genetic Predisposition to Disease Polymorphism, Single Nucleotide Humans
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Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium.

Circulation. Cardiovascular imaging Jun 1, 2018
BACKGROUND: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necess...
Aged Male Middle Aged Severity of Illness Index Prospective Studies Retrospective Studies Female Reproducibility of Results Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Coronary Vessels Asia Deep Learning United States Europe Predictive Value of Tests Humans Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial
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Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions.

IEEE transactions on medical imaging Feb 1, 2018
Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans acquired in screening enable quantification of atherosclerotic calcifications and thus enable identifi...
Lung Neoplasms Calcinosis Aortic Valve Stenosis Aortic Valve Coronary Artery Disease Coronary Vessels Radiography, Thoracic Algorithms Tomography, X-Ray Computed Humans Aged Neural Networks, Computer Middle Aged
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[Automated Classification of Calcification and Stent on Computed Tomography Coronary Angiography Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi Jan 1, 2018
In computed tomography coronary angiography (CTCA), calcification and stent make it difficult to evaluate intravascular lumen. This is a cause of low positive-predictive value of coronary stenosis. Therefore, it is expected to develop a computer-aide...
Computed Tomography Angiography Cardiomyopathies Tomography, X-Ray Computed Sensitivity and Specificity Humans Calcinosis Coronary Artery Disease Cross-Sectional Studies Coronary Angiography Stents Deep Learning Automation
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Plasma fatty acid profile as biomarker of coronary artery disease: a pilot study using fourth generation artificial neural networks.

Journal of biological regulators and homeostatic agents Jan 1, 2018
Many studies, focused on identifying new biomarkers for coronary artery disease (CAD) risk computation and monitoring, suggested a potential diagnostic role for fatty acids (FA). In the present study, we explored the potential diagnostic role of FA b...
Male Middle Aged Pilot Projects Neural Networks, Computer Coronary Artery Disease Biomarkers Aged Humans Sensitivity and Specificity Fatty Acids
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[Comparison of outcomes of two minimally invasive approaches for multi-vessel coronary revascularization].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences Dec 18, 2017
OBJECTIVE: To compare the safety and effectiveness of two minimally invasive approaches for multi-vessel coronary revascularization.
Mammary Arteries Coronary Angiography Myocardial Revascularization Humans Percutaneous Coronary Intervention Time Factors Coronary Artery Disease Treatment Outcome Coronary Artery Bypass Minimally Invasive Surgical Procedures
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Demonstration of the Safety and Feasibility of Robotically Assisted Percutaneous Coronary Intervention in Complex Coronary Lesions: Results of the CORA-PCI Study (Complex Robotically Assisted Percutaneous Coronary Intervention).

JACC. Cardiovascular interventions Jul 10, 2017
OBJECTIVES: The aims of this study were to evaluate the feasibility and technical success of robotically assisted percutaneous coronary intervention (R-PCI) for the treatment of coronary artery disease (CAD) in clinical practice, especially in comple...
Radiation Dosage Time Factors Aged Coronary Artery Disease Humans Logistic Models Male Radiography, Interventional Coronary Angiography Female Feasibility Studies Middle Aged Registries Treatment Outcome Stents Propensity Score Case-Control Studies Fluoroscopy Robotics Chi-Square Distribution Percutaneous Coronary Intervention
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Percutaneous coronary intervention using a combination of robotics and telecommunications by an operator in a separate physical location from the patient: an early exploration into the feasibility of telestenting (the REMOTE-PCI study).

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology Jan 20, 2017
AIMS: The present study explores the feasibility of telestenting, wherein a physician operator performs stenting on a patient in a separate physical location using a combination of robotics and telecommunications.
Telecommunications Angioplasty, Balloon, Coronary Humans Female Aged Coronary Angiography Male Aged, 80 and over Equipment Design Percutaneous Coronary Intervention Middle Aged Coronary Artery Disease Stents Treatment Outcome Robotics
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Evaluation of Machine Learning Methods to Predict Coronary Artery Disease Using Metabolomic Data.

Studies in health technology and informatics Jan 1, 2017
Metabolomic data can potentially enable accurate, non-invasive and low-cost prediction of coronary artery disease. Regression-based analytical approaches however might fail to fully account for interactions between metabolites, rely on a priori selec...
Logistic Models Models, Theoretical Humans Metabolomics Female Machine Learning Coronary Artery Disease Aged Male Middle Aged
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