… of CMR radiomics … CMR radiomics over existing approaches, we hierarchically built
supervised ML models incorporating traditional vascular risk factors (VRFs) and conventional CMR …

… yielded optimal results as the best machine learning algorithms for this radiomics analysis
study. This work showed that using radiomics on Cine-CMR images is helpful to accurately …

Objective To evaluate the potential value of the machine learning (ML) models using radiomic
features of late gadolinium enhancement (LGE) and cine images on magnetic resonance …

… We explored whether radiomic features from T1 maps by cardiac magnetic resonance (CMR)
could … ) undergoing a CMR scan were included in this study. We extracted a total of 850 …

… CMR images is another approach to TA in CMR imaging (11, 12). Hence, we hypothesized
that a radiomics … differences in the myocardial texture of CA and HCM on CMR cine images. …

… We will also review existing literature on CMR radiomics, … More commonly, machine learning
algorithms are used to train … machines (SVMs) are a commonly used machine learning …

… [29] investigated the potential of Cine-CMR radiomics for differentiating MI from normal … of
radiomic features extracted from LGE-CMR images along with machine learning algorithms to …

… cardiac diseases, the application of radiomics to CMR imaging data appears to be appealing
… The first applications of radiomics and TA in CMR have been reported for segmentation of …

… , the performance of cine CMR-based radiomics in predicting MACEs in … radiomics features
derived from cine CMR images and develop a predictive model using machine learning to …

… and brain diseases using CMR radiomics analysis may provide … In this paper, we used
CMR radiomics analysis to study … We used machine learning (ML) methods to identify the most …