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)

Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective. - Aly A. Mohamed; Yahong Luo; Hong Peng; Rachel C. Jankowitz; Shandong Wu (J. Digit. Imaging, 2018)

Can we boost the power of the Viola-Jones face detector using preprocessing? An empirical study. - Mahmoud Afifi; Marwa Nasser; Mostafa Korashy; Katherine Rohde; Aly A. Mohamed (J. Electronic Imaging, 2018)

Deep learning for identifying breast cancer malignancy and false recalls: a robustness study on training strategy. - Kadie Clancy; Lei Zhang; Aly A. Mohamed; Sarah S. Aboutalib; Wendie A. Berg; Shandong Wu (Computer-Aided Diagnosis, 2019)

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)

Automated deep-learning method for whole-breast segmentation in diffusion-weighted breast MRI. - Lei Zhang; Ruimei Chai; Aly A. Mohamed; Bingjie Zheng; Zhimeng Luo; Shandong Wu (Computer-Aided Diagnosis, 2019)

Multi-site Evaluation of a Study-Level Classifier for Mammography Using Deep Learning. - Dustin Sargent; Sun Young Park; Amod Jog; Aly A. Mohamed; David Richmond (MICCAI (6), 2020)

Deep Learning Pre-training Strategy for Mammogram Image Classification: an Evaluation Study. - Kadie Clancy; Sarah S. Aboutalib; Aly A. Mohamed; Jules H. Sumkin; Shandong Wu (J. Digit. Imaging, 2020)

Inaccurate Labels in Weakly-Supervised Deep Learning: Automatic Identification and Correction and Their Impact on Classification Performance. - Degan Hao; Lei Zhang 036; Jules H. Sumkin; Aly A. Mohamed; Shandong Wu (IEEE J. Biomed. Health Informatics, 2020)