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Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms.

, , , , , , , , , , , and . J. Digit. Imaging, 35 (6): 1708-1718 (2022)

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RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models., , , , , , , , , and 7 other author(s). CoRR, (2024)Overall Survival Prediction in Renal Cell Carcinoma Patients Using Computed Tomography Radiomic and Clinical Information., , , , , , , and . J. Digit. Imaging, 34 (5): 1086-1098 (2021)Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms., , , , , , , , , and 2 other author(s). J. Digit. Imaging, 35 (6): 1708-1718 (2022)Differentiation of COVID-19 pneumonia from other lung diseases using CT radiomic features and machine learning: A large multicentric cohort study., , , , , , , , , and 32 other author(s). Int. J. Imaging Syst. Technol., (March 2024)Medical Image Segmentation Review: The success of U-Net., , , , , , , , , and . CoRR, (2022)Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images., , , , , , , , , and . Comput. Biol. Medicine, (2022)COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14, 339 patients., , , , , , , , , and 39 other author(s). Comput. Biol. Medicine, (2022)