Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. - Dmitry Cherezov; Samuel H. Hawkins; Dmitry B. Goldgof; Lawrence O. Hall; Yoganand Balagurunathan; Robert J. Gillies; Matthew B. Schabath (SMC, 2016)

Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. - Saeed S. Alahmari; Dmitry Cherezov; Dmitry B. Goldgof; Lawrence O. Hall; Robert J. Gillies; Matthew B. Schabath (IEEE Access, 2018)

Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. - Rahul Paul; Dmitry Cherezov; Matthew B. Schabath; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (Computer-Aided Diagnosis, 2019)

Deep radiomics: deep learning on radiomics texture images. - Rahul Paul; Sherzod Kariev; Dmitry Cherezov; Matthew B. Schabath; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (Computer-Aided Diagnosis, 2021)

Resolving impact of technical and biological variability on the convolutional neural networks: evaluating chest x-ray scans. - Dmitry Cherezov; Vidya Sankar Viswanathan; Amit Gupta; Anant Madabhushi (Image Processing, 2023)

Rank acquisition impact on radiomics estimation (AсquIRE) in chest CT imaging: A retrospective multi-site, multi-use-case study. - Dmitry Cherezov; Vidya Sankar Viswanathan; Pingfu Fu; Amit Gupta; Anant Madabhushi (Comput. Methods Programs Biomed., 2024)