AIMC Topic: Coronary Artery Disease
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A novel algorithm developed using machine learning and a J-ACCESS database can estimate defect scores from myocardial perfusion single-photon emission tomography images.
Annals of nuclear medicine
Aug 29, 2024
BACKGROUND: Stress myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) has been used to diagnose and predict the prognoses of patients with coronary artery disease (CAD). An ongoing multicenter collaboration establis...
Deep learning model for intravascular ultrasound image segmentation with temporal consistency.
The international journal of cardiovascular imaging
Aug 27, 2024
This study was conducted to develop and validate a deep learning model for delineating intravascular ultrasound (IVUS) images of coronary arteries.Using a total of 1240 40-MHz IVUS pullbacks with 191,407 frames, the model for lumen and external elast...
Scale Mutualized Perception for Vessel Border Detection in Intravascular Ultrasound Images.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 9, 2024
Vessel border detection in IVUS images is essential for coronary disease diagnosis. It helps to obtain the clinical indices on the inner vessel morphology to indicate the stenosis. However, the existing methods suffer the challenge of scale-dependent...
Identification of potential biomarkers for atrial fibrillation and stable coronary artery disease based on WGCNA and machine algorithms.
BMC cardiovascular disorders
Aug 2, 2024
BACKGROUND: Patients with atrial fibrillation (AF) often have coronary artery disease (CAD), but the biological link between them remains unclear. This study aims to explore the common pathogenesis of AF and CAD and identify common biomarkers.
Development of machine learning models for fractional flow reserve prediction in angiographically intermediate coronary lesions.
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
Aug 1, 2024
BACKGROUND: Fractional flow reserve (FFR) represents the gold standard in guiding the decision to proceed or not with coronary revascularization of angiographically intermediate coronary lesion (AICL). Optical coherence tomography (OCT) allows to car...
Fractional Flow Reserve, Myocardial
Aged
Coronary Vessels
Male
Plaque, Atherosclerotic
Middle Aged
Cardiac Catheterization
Decision Support Techniques
Coronary Angiography
Severity of Illness Index
Coronary Stenosis
Databases, Factual
Coronary Artery Disease
Humans
Female
Predictive Value of Tests
Supervised Machine Learning
Software
Reproducibility of Results
Tomography, Optical Coherence
Predicting angiographic coronary artery disease using machine learning and high-frequency QRS.
BMC medical informatics and decision making
Jul 31, 2024
AIM: Exercise stress ECG is a common diagnostic test for stable coronary artery disease, but its sensitivity and specificity need to be further improved. In this paper, we construct a machine learning model for the prediction of angiographic coronary...
Deeper insights from deep learning: Enhanced myocardial perfusion assessments using multimodal artificial intelligence.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Jul 30, 2024
Evaluation of the Factors Influencing Blood Transfusion during Minimally Invasive Direct Coronary Artery Bypass Surgery.
Cardiology
Jul 26, 2024
INTRODUCTION: The objective of this study was to analyze the blood transfusion factors of minimally invasive direct coronary artery bypass (MIDCAB) surgery using artificial intelligence.
Reduced response to regadenoson with increased weight: An artificial intelligence-based quantitative myocardial perfusion study.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Jul 25, 2024
BACKGROUND: There is conflicting evidence regarding the response to a fixed dose of regadenoson in patients with high body weight. The aim of this study was to evaluate the effectiveness of regadenoson in patients with varying body weights using nove...
Adenosine A2 Receptor Agonists
Purines
Coronary Circulation
Myocardial Perfusion Imaging
Case-Control Studies
Adenosine
Logistic Models
Risk Factors
Humans
Obesity
Aged
Artificial Intelligence
Predictive Value of Tests
Male
Algorithms
Image Interpretation, Computer-Assisted
Middle Aged
Coronary Artery Disease
Female
Pyrazoles
Body Weight
Vasodilator Agents
Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors.
BMC medical informatics and decision making
Jul 22, 2024
OBJECTIVE: To develop and validate machine learning models for predicting coronary artery disease (CAD) within a Taiwanese cohort, with an emphasis on identifying significant predictors and comparing the performance of various models.
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