AIMC Topic: Coronary Artery Disease
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Deep Learning for Explainable Estimation of Mortality Risk From Myocardial Positron Emission Tomography Images.
Circulation. Cardiovascular imaging
Sep 20, 2022
BACKGROUND: We aim to develop an explainable deep learning (DL) network for the prediction of all-cause mortality directly from positron emission tomography myocardial perfusion imaging flow and perfusion polar map data and evaluate it using prospect...
Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events.
JACC. Cardiovascular imaging
Sep 14, 2022
BACKGROUND: Assessment of coronary artery calcium (CAC) by computed tomographic (CT) imaging provides an accurate measure of atherosclerotic burden. CAC is also visible in computed tomographic attenuation correction (CTAC) scans, always acquired with...
Polar map-free 3D deep learning algorithm to predict obstructive coronary artery disease with myocardial perfusion CZT-SPECT.
European journal of nuclear medicine and molecular imaging
Sep 14, 2022
PURPOSE: Deep learning (DL) models have been shown to outperform total perfusion deficit (TPD) quantification in predicting obstructive coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, previously published methods have ...
Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization.
Computers in biology and medicine
Sep 10, 2022
OBJECTIVE: Cardiovascular disease (CVD) is a major healthcare challenge and therefore early risk assessment is vital. Previous assessment techniques use either "conventional CVD risk calculators (CCVRC)" or machine learning (ML) paradigms. These tech...
Automatic Coronary Artery Segmentation of CCTA Images With an Efficient Feature-Fusion-and-Rectification 3D-UNet.
IEEE journal of biomedical and health informatics
Aug 11, 2022
Automatic coronary artery segmentation is of great value in diagnosing coronary disease. In this paper, we propose an automatic coronary artery segmentation method for coronary computerized tomography angiography (CCTA) images based on a deep convolu...
Routine Intensive Care May Be Selectively Skipped After Robotic Coronary Bypass.
The Annals of thoracic surgery
Aug 5, 2022
Deep learning exploration for SPECT MPI polar map images classification in coronary artery disease.
Annals of nuclear medicine
Jun 30, 2022
OBJECTIVE: The exploration and the implementation of a deep learning method using a state-of-the-art convolutional neural network for the classification of polar maps represent myocardial perfusion for the detection of coronary artery disease.
Explainable deep learning algorithm for distinguishing incomplete Kawasaki disease by coronary artery lesions on echocardiographic imaging.
Computer methods and programs in biomedicine
Jun 21, 2022
BACKGROUND AND OBJECTIVE: Incomplete Kawasaki disease (KD) has often been misdiagnosed due to a lack of the clinical manifestations of classic KD. However, it is associated with a markedly higher prevalence of coronary artery lesions. Identifying cor...
Using a deep learning algorithm to score coronary artery calcium in myocardial perfusion imaging: A real opportunity or just a new hype?
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Jun 20, 2022
Genetic Analysis of Coronary Artery Disease Using Tree-Based Automated Machine Learning Informed By Biology-Based Feature Selection.
IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2022
Machine Learning (ML) approaches are increasingly being used in biomedical applications. Important challenges of ML include choosing the right algorithm and tuning the parameters for optimal performance. Automated ML (AutoML) methods, such as Tree-ba...
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