AIMC Topic: Models, Cardiovascular

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A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis.

Journal of the Royal Society, Interface Jan 1, 2018
Structural finite-element analysis (FEA) has been widely used to study the biomechanics of human tissues and organs, as well as tissue-medical device interactions, and treatment strategies. However, patient-specific FEA models usually require complex...
Humans Computer Simulation Deep Learning Stress, Mechanical Aorta Finite Element Analysis Models, Cardiovascular
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Improving CCTA-based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation.

Medical physics Mar 1, 2017
PURPOSE: The goal of this study was to assess the potential added benefit of accounting for partial volume effects (PVE) in an automatic coronary lumen segmentation algorithm that is used to determine the hemodynamic significance of a coronary artery...
Humans Machine Learning Software Retrospective Studies Hemodynamics ROC Curve Imaging, Three-Dimensional Area Under Curve Coronary Angiography Datasets as Topic Coronary Vessels Pattern Recognition, Automated Computed Tomography Angiography Models, Cardiovascular Coronary Stenosis
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Using ordinal partition transition networks to analyze ECG data.

Chaos (Woodbury, N.Y.) Jul 1, 2016
Electrocardiogram (ECG) data from patients with a variety of heart conditions are studied using ordinal pattern partition networks. The ordinal pattern partition networks are formed from the ECG time series by symbolizing the data into ordinal patter...
Humans Neural Networks, Computer Databases, Factual Female Male Electrocardiography Pattern Recognition, Automated Models, Cardiovascular
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A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

Pakistan journal of pharmaceutical sciences Mar 1, 2016
Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each elect...
Humans Neural Networks, Computer Computer Simulation Animals Time Factors Action Potentials Heart Conduction System Arrhythmias, Cardiac Heart Rate Models, Cardiovascular
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