AIMC Topic: Models, Cardiovascular

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Neural Network Vessel Lumen Regression for Automated Lumen Cross-Section Segmentation in Cardiovascular Image-Based Modeling.

Cardiovascular engineering and technology Nov 11, 2020
PURPOSE: We accelerate a pathline-based cardiovascular model building method by training machine learning models to directly predict vessel lumen surface points from computed tomography (CT) and magnetic resonance (MR) medical image data.
Humans Neural Networks, Computer Reproducibility of Results Diagnosis, Computer-Assisted Computed Tomography Angiography Models, Cardiovascular Patient-Specific Modeling Blood Vessels Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Automation Magnetic Resonance Angiography
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Deep learning-based reduced order models in cardiac electrophysiology.

PloS one Oct 1, 2020
Predicting the electrical behavior of the heart, from the cellular scale to the tissue level, relies on the numerical approximation of coupled nonlinear dynamical systems. These systems describe the cardiac action potential, that is the polarization/...
Myocardial Ischemia Deep Learning Models, Cardiovascular Heart Electrophysiological Phenomena Nonlinear Dynamics
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Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning.

Scientific reports Sep 14, 2020
Cardiac and aortic characteristics are crucial for cardiovascular disease detection. However, noninvasive estimation of aortic hemodynamics and cardiac contractility is still challenging. This paper investigated the potential of estimating aortic sys...
Heart Aorta Models, Cardiovascular Myocardial Contraction Humans Machine Learning Hemodynamics
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Using intravascular ultrasound image-based fluid-structure interaction models and machine learning methods to predict human coronary plaque vulnerability change.

Computer methods in biomechanics and biomedical engineering Jul 22, 2020
Plaque vulnerability prediction is of great importance in cardiovascular research. In vivo follow-up intravascular ultrasound (IVUS) coronary plaque data were acquired from nine patients to construct fluid-structure interaction models to obtain plaqu...
Middle Aged Ultrasonography ROC Curve Imaging, Three-Dimensional Risk Factors Biomechanical Phenomena Male Linear Models Coronary Vessels Plaque, Atherosclerotic Models, Cardiovascular Support Vector Machine Area Under Curve Coronary Angiography Ultrasonography, Interventional Humans Machine Learning Female
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Classification of heart sounds based on the combination of the modified frequency wavelet transform and convolutional neural network.

Medical & biological engineering & computing Jul 7, 2020
We purpose a novel method that combines modified frequency slice wavelet transform (MFSWT) and convolutional neural network (CNN) for classifying normal and abnormal heart sounds. A hidden Markov model is used to find the position of each cardiac cyc...
Wavelet Analysis Models, Cardiovascular Biomedical Engineering Heart Sounds Phonocardiography Cardiovascular Diseases Diagnosis, Computer-Assisted Humans Signal Processing, Computer-Assisted Neural Networks, Computer Markov Chains Algorithms
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Missing Value Estimation Methods Research for Arrhythmia Classification Using the Modified Kernel Difference-Weighted KNN Algorithms.

BioMed research international Jun 21, 2020
Electrocardiogram (ECG) signal is critical to the classification of cardiac arrhythmia using some machine learning methods. In practice, the ECG datasets are usually with multiple missing values due to faults or distortion. Unfortunately, many establ...
Machine Learning Computational Biology Electrocardiography Electronic Data Processing Arrhythmias, Cardiac Humans Models, Cardiovascular
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Preprocedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation.

Circulation. Arrhythmia and electrophysiology Jun 14, 2020
BACKGROUND: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a m...
Recurrence Models, Cardiovascular Patient-Specific Modeling Pulmonary Veins Meglumine Heart Rate Catheter Ablation Proof of Concept Study Organometallic Compounds Action Potentials Predictive Value of Tests Atrial Fibrillation Retrospective Studies Aged Female Male Reproducibility of Results Middle Aged Humans Risk Factors Risk Assessment Machine Learning Diagnosis, Computer-Assisted Treatment Outcome Contrast Media Magnetic Resonance Imaging
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Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

PloS one May 21, 2020
Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of...
Boston Risk Factors Aged Male Stroke Humans Middle Aged Hematocrit Machine Learning Nonlinear Dynamics Algorithms Models, Cardiovascular Prospective Studies Female Risk Assessment Cohort Studies Electrocardiography Decision Trees
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Non - invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps.

Computer methods in biomechanics and biomedical engineering May 20, 2020
Cardiovascular diseases (CVD) and strokes produce immense health and economic burdens globally. Coronary Artery Disease (CAD) is the most common type of cardiovascular disease. Coronary Angiography, which is an invasive approach for detection and tre...
Humans Algorithms Female Male ROC Curve Decision Support Systems, Clinical Fuzzy Logic Coronary Artery Disease Databases as Topic Models, Cardiovascular
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Improving an Intelligent Detection System for Coronary Heart Disease Using a Two-Tier Classifier Ensemble.

BioMed research international Apr 27, 2020
Coronary heart disease (CHD) is one of the severe health issues and is one of the most common types of heart diseases. It is the most frequent cause of mortality across the globe due to the lack of a healthy lifestyle. Owing to the fact that a heart ...
Databases, Factual Diagnosis, Computer-Assisted Coronary Disease Models, Cardiovascular Humans Machine Learning
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