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Coronary Artery Disease

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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...

Machine learning and deep learning to predict mortality in patients with spontaneous coronary artery dissection.

Scientific reports
Machine learning (ML) and deep learning (DL) can successfully predict high prevalence events in very large databases (big data), but the value of this methodology for risk prediction in smaller cohorts with uncommon diseases and infrequent events is ...

Machine Learning with F-Sodium Fluoride PET and Quantitative Plaque Analysis on CT Angiography for the Future Risk of Myocardial Infarction.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Coronary F-sodium fluoride (F-NaF) PET and CT angiography-based quantitative plaque analysis have shown promise in refining risk stratification in patients with coronary artery disease. We combined both of these novel imaging approaches to develop an...

Contextual embedding bootstrapped neural network for medical information extraction of coronary artery disease records.

Medical & biological engineering & computing
Coronary artery disease (CAD) is the major cause of human death worldwide. The development of new CAD early diagnosis methods based on medical big data has a great potential to reduce the risk of CAD death. In this process, neural network (NN), as a ...

Cardiac Phase Space Analysis: Assessing Coronary Artery Disease Utilizing Artificial Intelligence.

BioMed research international
The bridge of artificial intelligence to cardiovascular medicine has opened up new avenues for novel diagnostics that may significantly enhance the cardiology care pathway. Cardiac phase space analysis is a noninvasive diagnostic platform that combin...