AIMC Topic: Myocardial Ischemia
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A deep learning-based fully automatic and clinical-ready framework for regional myocardial segmentation and myocardial ischemia evaluation.
Medical & biological engineering & computing
Feb 11, 2023
Myocardial ischemia diagnosis with CT perfusion imaging (CTP) is important in coronary artery disease management. Traditional analysis procedure is time-consuming and error-prone due to the semi-manual and operator-dependent nature. To improve the di...
Deep learning for myocardial ischemia auxiliary diagnosis using CZT SPECT myocardial perfusion imaging.
Journal of the Chinese Medical Association : JCMA
Oct 28, 2022
BACKGROUND: The World Health Organization reported that cardiovascular disease is the most common cause of death worldwide. On average, one person dies of heart disease every 26 min worldwide. Deep learning approaches are characterized by the appropr...
Stable patients with suspected myocardial ischemia: comparison of machine-learning computed tomography-based fractional flow reserve and stress perfusion cardiovascular magnetic resonance imaging to detect myocardial ischemia.
BMC cardiovascular disorders
Feb 5, 2022
BACKGROUND: Machine-Learning Computed Tomography-Based Fractional Flow Reserve (CT-FFR) is a novel tool for the assessment of hemodynamic relevance of coronary artery stenoses. We examined the diagnostic performance of CT-FFR compared to stress perfu...
A Comparison among Different Machine Learning Pretest Approaches to Predict Stress-Induced Ischemia at PET/CT Myocardial Perfusion Imaging.
Computational and mathematical methods in medicine
Nov 27, 2021
Traditional approach for predicting coronary artery disease (CAD) is based on demographic data, symptoms such as chest pain and dyspnea, and comorbidity related to cardiovascular diseases. Usually, these variables are analyzed by logistic regression ...
Computational Biology
Logistic Models
Coronary Artery Disease
Support Vector Machine
Aged
Predictive Value of Tests
Decision Trees
Humans
Myocardial Ischemia
Male
Bayes Theorem
Myocardial Perfusion Imaging
Machine Learning
Middle Aged
Positron Emission Tomography Computed Tomography
Algorithms
Cohort Studies
Exercise Test
Female
Exploring the diagnostic effectiveness for myocardial ischaemia based on CCTA myocardial texture features.
BMC cardiovascular disorders
Aug 31, 2021
BACKGROUND: To explore the characteristics of myocardial textures on coronary computed tomography angiography (CCTA) images in patients with coronary atherosclerotic heart disease, a classification model was established, and the diagnostic effectiven...
Proof of Concept Study
Myocardial Ischemia
Multidetector Computed Tomography
Computed Tomography Angiography
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Humans
Machine Learning
Retrospective Studies
Female
Reproducibility of Results
Aged
Male
Middle Aged
Coronary Microvascular Dysfunction and the Risk of Atrial Fibrillation From an Artificial Intelligence-Enabled Electrocardiogram.
Circulation. Arrhythmia and electrophysiology
Aug 16, 2021
Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.
JAMA network open
May 3, 2021
IMPORTANCE: Anticipating the risk of gastrointestinal bleeding (GIB) when initiating antithrombotic treatment (oral antiplatelets or anticoagulants) is limited by existing risk prediction models. Machine learning algorithms may result in superior pre...
Humans
Antifibrinolytic Agents
Gastrointestinal Hemorrhage
Myocardial Ischemia
Thienopyridines
Cross-Sectional Studies
Fibrinolytic Agents
Male
Anticoagulants
Aged
Middle Aged
Atrial Fibrillation
Risk Assessment
Venous Thromboembolism
Adolescent
Aged, 80 and over
Machine Learning
Cohort Studies
Young Adult
Retrospective Studies
United States
Adult
Clinical Decision-Making
Predictive Value of Tests
Female
An Automated High-Accuracy Detection Scheme for Myocardial Ischemia Based on Multi-Lead Long-Interval ECG and Choi-Williams Time-Frequency Analysis Incorporating a Multi-Class SVM Classifier.
Sensors (Basel, Switzerland)
Mar 26, 2021
Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital for the prevention of medical complications related to the heart, as they can lead to heart muscle de...
Emerging methods for the characterization of ischemic heart disease: ultrafast Doppler angiography, micro-CT, photon-counting CT, novel MRI and PET techniques, and artificial intelligence.
European radiology experimental
Mar 25, 2021
After an ischemic event, disruptive changes in the healthy myocardium may gradually develop and may ultimately turn into fibrotic scar. While these structural changes have been described by conventional imaging modalities mostly on a macroscopic scal...
Low-dose PET image noise reduction using deep learning: application to cardiac viability FDG imaging in patients with ischemic heart disease.
Physics in medicine and biology
Feb 25, 2021
INTRODUCTION: Cardiac [F]FDG-PET is widely used for viability testing in patients with chronic ischemic heart disease. Guidelines recommend injection of 200-350 MBq [F]FDG, however, a reduction of radiation exposure has become increasingly important,...
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