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A digitally assisted technique to improve rectifier efficiency in wireless energy harvesting systems., , , , and . ICCE, page 103-104. IEEE, (2016)COLI-Net: Deep learning-assisted fully automated COVID-19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images., , , , , , , , , and 6 other author(s). Int. J. Imaging Syst. Technol., 32 (1): 12-25 (2022)Non-contrast Cine Cardiac Magnetic Resonance image radiomics features and machine learning algorithms for myocardial infarction detection., , , , , , , , , and 1 other author(s). Comput. Biol. Medicine, (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)PET/CT Radiomic Sequencer for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients., , , , , , , and . CoRR, (2019)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)Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients., , , , , , , , , and 6 other author(s). Comput. Biol. Medicine, (2021)Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches., , , , , , , and . CoRR, (2019)Implementation of an FPGA-based low-power video processing module for a head-mounted display system., , , , and . ICCE, page 214-217. IEEE, (2013)