Area of research
Artificial Intelligence · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Medicine, Mammography, Breast cancer, Artificial intelligence, Computer science, and Phenotype.
Subgroup evaluation to understand performance gaps in deep learning-based classification of regions of interest on mammography
Impact of multi-source data augmentation on performance of convolutional neural networks for abnormality classification in mammography
External Validation of a Mammography-Derived AI-Based Risk Model in a U.S. Breast Cancer Screening Cohort of White and Black Women
Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets
Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction
Carotid Wall Longitudinal Motion in Ultrasound Imaging: An Expert Consensus Review
Radiomic Phenotypes of Mammographic Parenchymal Complexity: Toward Augmenting Breast Density in Breast Cancer Risk Assessment