AIMC Topic: Myocardial Ischemia

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Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis.

BioMed research international Dec 16, 2020
Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA anal...
Plaque, Atherosclerotic Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Calcium Coronary Vessels Myocardial Ischemia Risk Artificial Intelligence Machine Learning Algorithms Phenotype Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Coronary Artery Disease Prognosis Middle Aged Humans
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Detecting myocardial scar using electrocardiogram data and deep neural networks.

Biological chemistry Oct 2, 2020
Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischae...
Humans Deep Learning Electrocardiography Cicatrix Neural Networks, Computer Myocardium Female Myocardial Ischemia Male Middle Aged
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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/...
Deep Learning Heart Nonlinear Dynamics Myocardial Ischemia Models, Cardiovascular Electrophysiological Phenomena
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Machine learning-based classification and diagnosis of clinical cardiomyopathies.

Physiological genomics Aug 3, 2020
Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common types of cardiomyopathies leading to heart failure. Accurate diagnostic classification of different types of cardiomyopathies is critical for precision medicine in clinical...
Heart Failure Myocardial Ischemia Cardiomyopathies Machine Learning Transcriptome Computational Biology Databases, Genetic Humans Artificial Intelligence
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Substrate Spatial Complexity Analysis for the Prediction of Ventricular Arrhythmias in Patients With Ischemic Cardiomyopathy.

Circulation. Arrhythmia and electrophysiology Mar 18, 2020
BACKGROUND: Transition zones between healthy myocardium and scar form a spatially complex substrate that may give rise to reentrant ventricular arrhythmias (VAs). We sought to assess the utility of a novel machine learning approach for quantifying 3-...
Humans Machine Learning Prognosis Male Ventricular Function, Left Stroke Volume Middle Aged Risk Assessment Retrospective Studies Female Risk Factors Aged Arrhythmias, Cardiac Death, Sudden, Cardiac Heart Rate Magnetic Resonance Imaging Myocardial Ischemia Diagnosis, Computer-Assisted Action Potentials Cardiomyopathies Fourier Analysis Imaging, Three-Dimensional Predictive Value of Tests United States Gadolinium DTPA Registries Contrast Media
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Super-resolution of cardiac magnetic resonance images using Laplacian Pyramid based on Generative Adversarial Networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 3, 2020
BACKGROUND AND OBJECTIVE: Cardiac magnetic resonance imaging (MRI) can assist in both functional and structural analysis of the heart, but due to hardware and physical limitations, high-resolution MRI scans is time consuming and peak signal-to-noise ...
Myocardial Ischemia Magnetic Resonance Imaging Myocardial Infarction Image Enhancement Signal-To-Noise Ratio Humans Neural Networks, Computer Image Processing, Computer-Assisted
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The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning-based FFR, or high-risk plaque features?

European radiology Mar 22, 2019
OBJECTIVES: The present study aimed to compare the diagnostic performance of a machine learning (ML)-based FFR algorithm, quantified subtended myocardial volume, and high-risk plaque features for predicting if a coronary stenosis is hemodynamically s...
Retrospective Studies Tomography, X-Ray Computed Female Humans Machine Learning Plaque, Atherosclerotic Coronary Stenosis Fractional Flow Reserve, Myocardial Male Middle Aged Coronary Angiography Myocardial Ischemia
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Development and testing of a deep learning-based strategy for scar segmentation on CMR-LGE images.

Magma (New York, N.Y.) Nov 20, 2018
OBJECTIVE: The aim of this paper is to investigate the use of fully convolutional neural networks (FCNNs) to segment scar tissue in the left ventricle from cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) images.
Gadolinium Image Enhancement Myocardial Ischemia Humans Contrast Media Female Neural Networks, Computer Magnetic Resonance Imaging Male Retrospective Studies Cicatrix Deep Learning Heart Ventricles
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Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation.

PLoS medicine Nov 13, 2018
BACKGROUND: Invasive fractional flow reserve (FFR) is a standard tool for identifying ischemia-producing coronary stenosis. However, in clinical practice, over 70% of treatment decisions still rely on visual estimation of angiographic stenosis, which...
Myocardial Ischemia Cardiac Catheterization Coronary Stenosis Fractional Flow Reserve, Myocardial Humans Coronary Angiography Ultrasonography, Interventional Middle Aged Republic of Korea Radiographic Image Interpretation, Computer-Assisted Machine Learning Severity of Illness Index Reproducibility of Results Female Coronary Vessels Prognosis Diagnosis, Computer-Assisted Aged Retrospective Studies Predictive Value of Tests Male Clinical Decision-Making
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Magnetocardiography-Based Ischemic Heart Disease Detection and Localization Using Machine Learning Methods.

IEEE transactions on bio-medical engineering Oct 23, 2018
OBJECTIVE: This study focused on developing a fast and accurate automatic ischemic heart disease detection/localization methodology.
Humans Myocardial Ischemia Machine Learning Magnetocardiography Diagnosis, Computer-Assisted Adult Coronary Stenosis Support Vector Machine Male Signal Processing, Computer-Assisted Heart
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