Assessment of the relationship between lesion segmentation accuracy and computer-aided diagnosis scheme performance. - Bin Zheng 001; Jiantao Pu; Sang Cheol Park; Margarita L. Zuley; David Gur (Computer-Aided Diagnosis, 2008)

Signal enhancement ratio (SER) quantified from breast DCE-MRI and breast cancer risk. - Shandong Wu; Brenda F. Kurland; Wendie A. Berg; Margarita L. Zuley; Rachel C. Jankowitz; Jules H. Sumkin; David Gur (Computer-Aided Diagnosis, 2015)

Do pre-trained deep learning models improve computer-aided classification of digital mammograms? - Sarah S. Aboutalib; Aly A. Mohamed; Margarita L. Zuley; Wendie A. Berg; Yahong Luo; Shandong Wu (Computer-Aided Diagnosis, 2018)

Can a limited double reading/second opinion of initially recalled breast ultrasound screening examinations improve radiologists' performances? - David Gur; Kimberly Harnist; Terri-Ann Gizienski; Margarita L. Zuley; Christiane M. Hakim; Amy Lu; Jules H. Sumkin; Gordon Abrams; Marie A. Ganott; Amy E. Kelly; Cathy S. Tyma; Thomas S. Chang; et al. (Image Perception, Observer Performance, and Technology Assessment, 2018)

Deep learning of sub-regional breast parenchyma in mammograms for localized breast cancer risk prediction. - Giacomo Nebbia; Aly A. Mohamed; Ruimei Chai; Bingjie Zheng; Margarita L. Zuley; Shandong Wu (Computer-Aided Diagnosis, 2019)

Oculomotor behaviour of radiologists reading digital breast tomosynthesis (DBT). - Nicholas M. D'Ardenne; Robert M. Nishikawa; Margarita L. Zuley; Chia-Chien Wu; Jeremy M. Wolfe (Image Perception, Observer Performance, and Technology Assessment, 2019)

Estimating near term breast cancer risk from sequential mammograms using deep learning, radon cumulative distribution transform, and a clinical risk factor: preliminary analysis. - Juhun Lee; Robert M. Nishikawa; Andriy Bandos; Margarita L. Zuley (Computer-Aided Diagnosis, 2021)

Multi-task learning to incorporate clinical knowledge into deep learning for breast cancer diagnosis. - Giacomo Nebbia; Dooman Arefan; Margarita L. Zuley; Jules H. Sumkin; Shandong Wu (Computer-Aided Diagnosis, 2021)

Radiomics-Informed Deep Curriculum Learning for Breast Cancer Diagnosis. - Giacomo Nebbia; Saba Dadsetan; Dooman Arefan; Margarita L. Zuley; Jules H. Sumkin; Heng Huang; Shandong Wu (MICCAI (5), 2021)

Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification. - Long Gao; Chang Liu; Dooman Arefan; Ashok Panigrahy; Margarita L. Zuley; Shandong Wu (CoRR, 2021)

Deep curriculum learning in task space for multi-class based mammography diagnosis. - Jun Luo 010; Dooman Arefan; Margarita L. Zuley; Jules H. Sumkin; Shandong Wu (Computer-Aided Diagnosis, 2022)

Deep learning of longitudinal mammogram examinations for breast cancer risk prediction. - Saba Dadsetan; Dooman Arefan; Wendie A. Berg; Margarita L. Zuley; Jules H. Sumkin; Shandong Wu (Pattern Recognit., 2022)

Medical knowledge-guided deep learning for mammographic breast density classification. - Long Gao; Chang Liu; Dooman Arefan; Ashok Panigrahy; Margarita L. Zuley; Shandong Wu (Computer-Aided Diagnosis, 2023)

Knowledge-Guided Multi-Task Learning for Breast Cancer Diagnosis Using Longitudinal Mammogram Images. - Zhengbo Zhou; Dooman Arefan; Margarita L. Zuley; Degan Hao; Jules H. Sumkin; Shandong Wu (ISBI, 2024)

Safe Breast Cancer Diagnosis Resilient to Mammographic Adversarial Samples. - Degan Hao; Dooman Arefan; Margarita L. Zuley; Wendie A. Berg; Shandong Wu (Deep-Breath@MICCAI, 2024)

Adversarially Robust Feature Learning for Breast Cancer Diagnosis. - Degan Hao; Dooman Arefan; Margarita L. Zuley; Wendie A. Berg; Shandong Wu (CoRR, 2024)

Longitudinal Mammogram Exam-based Breast Cancer Diagnosis Models: Vulnerability to Adversarial Attacks. - Zhengbo Zhou; Degan Hao; Dooman Arefan; Margarita L. Zuley; Jules H. Sumkin; Shandong Wu (CoRR, 2024)

Longmambattn: A Novel Architecture for Enhanced Breast Cancer Risk Prediction Using Variable-Length Longitudinal Mammograms. - Zhengbo Zhou; Dooman Arefan; Margarita L. Zuley; Jules H. Sumkin; Shandong Wu (ISBI, 2025)

STA-Risk: A Deep Dive of Spatio-Temporal Asymmetries for Breast Cancer Risk Prediction. - Zhengbo Zhou; Dooman Arefan; Margarita L. Zuley; Jules H. Sumkin; Shandong Wu (CoRR, 2025)