Prediction of coronary thin-cap fibroatheroma by intravascular ultrasound-based machine learning.
Journal:
Atherosclerosis
Published Date:
Sep 1, 2019
Abstract
BACKGROUND AND AIMS: Although grayscale intravascular ultrasound (IVUS) is commonly used for assessing coronary lesion morphology and optimizing stent implantation, detection of vulnerable plaques by IVUS remains challenging. We aimed to develop machine learning (ML) models for predicting optical coherence tomography-derived thin-cap fibroatheromas (OCT-TCFAs).
Authors
Keywords
Aged
Bayes Theorem
Coronary Artery Disease
Coronary Stenosis
Coronary Vessels
Diagnosis, Computer-Assisted
Disease Progression
Female
Fibrosis
Humans
Image Interpretation, Computer-Assisted
Machine Learning
Male
Middle Aged
Neural Networks, Computer
Plaque, Atherosclerotic
Predictive Value of Tests
Reproducibility of Results
Risk Assessment
Risk Factors
Rupture, Spontaneous
Tomography, Optical Coherence
Ultrasonography, Interventional