… This study explored the use of radiomic analysis of LGE-CMR images in patients with … the
optimization of the radiomic analysis and machine learning approaches. MGT facilitated the …

… of machine learning models optimised for disease discrimination using CMR radiomics …
In this study, we demonstrate the utility of CMR radiomics analysis as a tool for detailed …

… LD wrote python code and helped to modify it and provide essential guidance on how to
perform the optimization of the radiomic analysis and machine learning approaches. MT …

… of radiomics features of cardiac magnetic resonance (CMR) … We aim to evaluate whether
radiomics features of CMR cine … the reproducibility of radiomics features of CMR cine images. …

… tracking (CMR-FT) in these patients (p). Our aim was to analyze the usefulness of CMR-FT in
… They were studied with CMR including global longitudinal strain (GLS) using the Qstrain FT …

… propose machine learning (ML) techniques with CMR radiomics … radiomics with Logistic
Regression achieving an AUC of 0.72. Additionally, the rich phenotypic characterization of CMR …

… Radiomics and machine learning analysis could be a … The purpose of this study is to evaluate
the validity of Radiomics, … segments, in order to reduce CMR scan times in patients with …

… evaluated CMR radiomics studies using these three sets of guidelines. Therefore, the purpose
of this study was to assess the quality of radiomics studies using CMR with RQS, TRIPOD …

… CMR radiomics-based machine learning algorithm with a mean accuracy of 80%, and Martini
et al. (42) developed a deep learning … In this study, a radiomic-based machine learning …

… mode, radiomics can extract microscopic information from images for quantitative analysis.
The selected features and machine learning … In summary, radiomics based on CMR has made …