ArticleJournal of digital imaging2022
Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms.
Article in Journal of digital imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- AI Applied to Cardiac Magnetic Resonance for Precision Medicine in Coronary Artery Disease: A Systematic Review.Journal of cardiovascular development and disease · 2025Review
- Interpretable Radiomic Signature for Breast Microcalcification Detection and Classification.Journal of imaging informatics in medicine · 2024Article
- Enhancing Prediction of Myocardial Recovery After Coronary Revascularization: Integrating Radiomics from Myocardial Contrast Echocardiography with Machine Learning.International journal of general medicine · 2024Article
- Left Ventricular Myocardial Dysfunction Evaluation in Thalassemia Patients Using Echocardiographic Radiomic Features and Machine Learning Algorithms.Journal of digital imaging · 2023Article
- Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study.Scientific reports · 2023Article
- Post-revascularization Ejection Fraction Prediction for Patients Undergoing Percutaneous Coronary Intervention Based on Myocardial Perfusion SPECT Imaging Radiomics: a Preliminary Machine Learning Study.Journal of digital imaging · 2023Article
- Myocardial Perfusion SPECT Imaging Radiomic Features and Machine Learning Algorithms for Cardiac Contractile Pattern Recognition.Journal of digital imaging · 2023Article
- Machine learning-based prediction of 1-year mortality in hypertensive patients undergoing coronary revascularization surgery.Clinical cardiology · 2023Article
- Artificial Intelligence in Cardiovascular CT and MR Imaging.Life (Basel, Switzerland) · 2023Review
- On the Analyses of Medical Images Using Traditional Machine Learning Techniques and Convolutional Neural Networks.Archives of computational methods in engineering : state of the art reviews · 2023Article
- High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The main aim of the present study was to predict myocardial function improvement in cardiac MR (LGE-CMR) images in patients after coronary artery bypass grafting (CABG) using radiomics and machine learning algorithms. Altogether, 43 patients who had visible scars on short-axis LGE-CMR images and were candidates for CABG surgery were selected and enrolled in this study. MR imaging was performed preoperatively using a 1.5-T MRI scanner. All images were segmented by two expert radiologists (in consensus). Prior to extraction of radiomics features, all MR images were resampled to an isotropic voxel size of 1.8 × 1.8 × 1.8 mm
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.