Performance comparison of quantitative semantic features and lung-RADS in the National Lung Screening Trial. - Qian Li; Yoganand Balagurunathan; Ying Liu; Matthew B. Schabath; Robert J. Gillies (Image Perception, Observer Performance, and Technology Assessment, 2016)

Quantitative imaging features to predict cancer status in lung nodules. - Ying Liu; Yoganand Balagurunathan; Thomas Atwater; Sanja Antic; Qian Li; Ronald Walker; Gary T. Smith; Pierre P. Massion; Matthew B. Schabath; Robert J. Gillies (Image Perception, Observer Performance, and Technology Assessment, 2016)

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)

Predicting Nodule Malignancy using a CNN Ensemble Approach. - Rahul Paul; Lawrence O. Hall; Dmitry B. Goldgof; Matthew B. Schabath; Robert J. Gillies (IJCNN, 2018)

Representation of Deep Features using Radiologist defined Semantic Features. - Rahul Paul; Ying Liu; Qian Li; Lawrence O. Hall; Dmitry B. Goldgof; Yoganand Balagurunathan; Matthew B. Schabath; Robert J. Gillies (IJCNN, 2018)

Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients. - Wei Mu; Jin Qi; Hong Lu; Matthew B. Schabath; Yoganand Balagurunathan; Ilke Tunali; Robert James Gillies (Computer-Aided Diagnosis, 2018)

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)

Mitigating Adversarial Attacks on Medical Image Understanding Systems. - Rahul Paul; Matthew B. Schabath; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (ISBI, 2020)

Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future. - Rahul Paul; Matthew B. Schabath; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (Comput. Biol. Medicine, 2020)

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)

Survival time prediction from unannotated lung cancer histopathology images. - Nikolai Fetisov; Lawrence O. Hall; Dmitry B. Goldgof; Matthew B. Schabath (Digital and Computational Pathology, 2022)

Iam hiQ - a novel pair of accuracy indices for imputed genotypes. - Albert Rosenberger; Viola Tozzi; Heike Bickeböller; Rayjean J. Hung; David C. Christiani; Neil E. Caporaso; Geoffrey Liu; Stig E. Bojesen; Loic Le Marchand; Demetrios Albanes; Melinda C. Aldrich; Adonina Tardon; et al. (BMC Bioinform., 2022)

Unsupervised Prostate Cancer Histopathology Image Segmentation via Meta-Learning. - Nikolai Fetisov; Lawrence O. Hall; Dmitry B. Goldgof; Matthew B. Schabath (CBMS, 2023)

SeNMo: A Self-Normalizing Deep Learning Model for Enhanced Multi-Omics Data Analysis in Oncology. - Asim Waqas; Aakash Tripathi; Sabeen Ahmed; Ashwin Mukund; Hamza Farooq; Matthew B. Schabath; Paul Stewart; Mia Naeini; Ghulam Rasool 001 (CoRR, 2024)

Privacy Preserving Federated Learning in Medical Imaging with Uncertainty Estimation. - Nikolas Koutsoubis; Yasin Yilmaz; Ravi P. Ramachandran; Matthew B. Schabath; Ghulam Rasool 001 (CoRR, 2024)

Future-Proofing Medical Imaging with Privacy-Preserving Federated Learning and Uncertainty Quantification: A Review. - Nikolas Koutsoubis; Asim Waqas; Yasin Yilmaz; Ravi P. Ramachandran; Matthew B. Schabath; Ghulam Rasool 001 (CoRR, 2024)

Multimodal AI-driven Biomarker for Early Detection of Cancer Cachexia. - Sabeen Ahmed; Nathan Parker; Margaret Park; Evan W. Davis; Jennifer B. Permuth; Matthew B. Schabath; Yasin Yilmaz; Ghulam Rasool 001 (CoRR, 2025)

Reliable Radiologic Skeletal Muscle Area Assessment - A Biomarker for Cancer Cachexia Diagnosis. - Sabeen Ahmed; Nathan Parker; Margaret Park; Daniel Jeong; Lauren Peres; Evan W. Davis; Jennifer B. Permuth; Erin Siegel; Matthew B. Schabath; Yasin Yilmaz; Ghulam Rasool 001 (CoRR, 2025)

EAGLE: Efficient Alignment of Generalized Latent Embeddings for Multimodal Survival Prediction with Interpretable Attribution Analysis. - Aakash Tripathi; Asim Waqas; Matthew B. Schabath; Yasin Yilmaz; Ghulam Rasool 001 (CoRR, 2025)