AIMC Topic: Coronary Artery Disease

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Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction.

Nature communications
A promise of genomics in precision medicine is to provide individualized genetic risk predictions. Polygenic risk scores (PRS), computed by aggregating effects from many genomic variants, have been developed as a useful tool in complex disease resear...

Exploring the diagnostic effectiveness for myocardial ischaemia based on CCTA myocardial texture features.

BMC cardiovascular disorders
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...

Deep Learning Algorithm Predicts Angiographic Coronary Artery Disease in Stable Patients Using Only a Standard 12-Lead Electrocardiogram.

The Canadian journal of cardiology
BACKGROUND: Current electrocardiogram analysis algorithms cannot predict the presence of coronary artery disease (CAD), especially in stable patients. This study assessed the ability of an artificial intelligence algorithm (ECGio; HEARTio Inc, Pittsb...

Automatic detection of vessel structure by deep learning using intravascular ultrasound images of the coronary arteries.

PloS one
Intravascular ultrasound (IVUS) is a diagnostic modality used during percutaneous coronary intervention. However, specialist skills are required to interpret IVUS images. To address this issue, we developed a new artificial intelligence (AI) program ...

Deep learning powered coronary CT angiography for detecting obstructive coronary artery disease: The effect of reader experience, calcification and image quality.

European journal of radiology
OBJECTIVES: To investigate the effect of reader experience, calcification and image quality on the performance of deep learning (DL) powered coronary CT angiography (CCTA) in automatically detecting obstructive coronary artery disease (CAD) with inva...

Automated classification of coronary atherosclerotic plaque in optical frequency domain imaging based on deep learning.

Atherosclerosis
BACKGROUND AND AIMS: We developed a deep learning (DL) model for automated atherosclerotic plaque categorization using optical frequency domain imaging (OFDI) and performed quantitative and visual evaluations.

Outcomes of robotic coronary artery bypass versus nonrobotic coronary artery bypass.

Journal of cardiac surgery
BACKGROUND: Robotic coronary artery bypass graft (CABG) has developed in recent decades, however, prior studies showed conflicting result of robotic CABG compared to nonrobotic CABG in terms of mortality, morbidity, and cost. Herein, we sought to ana...

Commentary: When will the robots come marching in?

Journal of cardiac surgery
Minimally invasive techniques for coronary artery bypass grafting (CABG), specifically robotic-assisted CABG has increased in popularity despite conflicting evidence. Here, we review a report by Yokoyama and colleagues to the Journal of Cardiac Surge...

A deep learning-based model for characterization of atherosclerotic plaque in coronary arteries using optical coherence tomography  images.

Medical physics
PURPOSE: Coronary artery events are mainly associated with atherosclerosis in adult population, which is recognized as accumulation of plaques in arterial wall tissues. Optical Coherence Tomography (OCT) is a light-based imaging system used in cardio...