Matthew B. Schabath

21 papers B 4Journal 10Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	EAGLE: Efficient Alignment of Generalized Latent Embeddings for Multimodal Survival Prediction with Interpretable Attribution Analysis. CoRR Aakash Tripathi, Asim Waqas, Matthew B. Schabath, Yasin Yilmaz, Ghulam Rasool
2025	J	`jnl`	HONeYBEE: enabling scalable multimodal AI in oncology through foundation model-driven embeddings. npj Digit. Medicine Aakash Tripathi, Asim Waqas, Matthew B. Schabath, Yasin Yilmaz, Ghulam Rasool
2025	J	`jnl`	Multimodal AI-driven Biomarker for Early Detection of Cancer Cachexia. CoRR Sabeen Ahmed, Nathan Parker, Margaret Park, Evan W. Davis, Jennifer B. Permuth, Matthew B. Schabath, Yasin Yilmaz, Ghulam Rasool
2025	J	`jnl`	Reliable Radiologic Skeletal Muscle Area Assessment - A Biomarker for Cancer Cachexia Diagnosis. CoRR 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
2024	J	`jnl`	Future-Proofing Medical Imaging with Privacy-Preserving Federated Learning and Uncertainty Quantification: A Review. CoRR Nikolas Koutsoubis, Asim Waqas, Yasin Yilmaz, Ravi P. Ramachandran, Matthew B. Schabath, Ghulam Rasool
2024	J	`jnl`	Privacy Preserving Federated Learning in Medical Imaging with Uncertainty Estimation. CoRR Nikolas Koutsoubis, Yasin Yilmaz, Ravi P. Ramachandran, Matthew B. Schabath, Ghulam Rasool
2024	J	`jnl`	SeNMo: A Self-Normalizing Deep Learning Model for Enhanced Multi-Omics Data Analysis in Oncology. CoRR Asim Waqas, Aakash Tripathi, Sabeen Ahmed, Ashwin Mukund, Hamza Farooq, Matthew B. Schabath, Paul Stewart, Mia Naeini, Ghulam Rasool
2023	B	`conf`	Unsupervised Prostate Cancer Histopathology Image Segmentation via Meta-Learning. CBMS Nikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath
2022	J	`jnl`	Iam hiQ - a novel pair of accuracy indices for imputed genotypes. BMC Bioinform. 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, Guillermo Fernández-Tardón, Gad Rennert, John K. Field, Mike Davies, Triantafillos Liloglou, Lambertus A. Kiemeney, Philip Lazarus, Aage Haugen, Shanbeh Zienolddiny, Stephen Lam, Matthew B. Schabath, Angeline S. Andrew, Eric J. Duell, Susanne M. Arnold, Hans Brunnström, Olle Melander, Gary E. Goodman, Chu Chen, Jennifer A. Doherty, Marion Dawn Teare, Angela Cox, Penella J. Woll, Angela Risch, Thomas R. Muley, Mikael Johansson, Paul Brennan, Maria Teresa Landi, Sanjay Shete, Christopher I. Amos
2022	—	`conf`	Survival time prediction from unannotated lung cancer histopathology images. Digital and Computational Pathology Nikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath
2021	—	`conf`	Deep radiomics: deep learning on radiomics texture images. Computer-Aided Diagnosis Rahul Paul, Sherzod Kariev, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
2020	J	`jnl`	Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future. Comput. Biol. Medicine Rahul Paul, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
2020	—	`conf`	Mitigating Adversarial Attacks on Medical Image Understanding Systems. ISBI Rahul Paul, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
2019	—	`conf`	Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. Computer-Aided Diagnosis Rahul Paul, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
2018	J	`jnl`	Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. IEEE Access Saeed S. Alahmari, Dmitry Cherezov, Dmitry B. Goldgof, Lawrence O. Hall, Robert J. Gillies, Matthew B. Schabath
2018	B	`conf`	Predicting Nodule Malignancy using a CNN Ensemble Approach. IJCNN Rahul Paul, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath, Robert J. Gillies
2018	—	`conf`	Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients. Computer-Aided Diagnosis Wei Mu, Jin Qi, Hong Lu, Matthew B. Schabath, Yoganand Balagurunathan, Ilke Tunali, Robert James Gillies
2018	B	`conf`	Representation of Deep Features using Radiologist defined Semantic Features. IJCNN Rahul Paul, Ying Liu, Qian Li, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Matthew B. Schabath, Robert J. Gillies
2016	B	`conf`	Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. SMC Dmitry Cherezov, Samuel H. Hawkins, Dmitry B. Goldgof, Lawrence O. Hall, Yoganand Balagurunathan, Robert J. Gillies, Matthew B. Schabath
2016	—	`conf`	Performance comparison of quantitative semantic features and lung-RADS in the National Lung Screening Trial. Image Perception, Observer Performance, and Technology Assessment Qian Li, Yoganand Balagurunathan, Ying Liu, Matthew B. Schabath, Robert J. Gillies
2016	—	`conf`	Quantitative imaging features to predict cancer status in lung nodules. Image Perception, Observer Performance, and Technology Assessment Ying Liu, Yoganand Balagurunathan, Thomas Atwater, Sanja Antic, Qian Li, Ronald Walker, Gary T. Smith, Pierre P. Massion, Matthew B. Schabath, Robert J. Gillies