74 citations · 112 across the 3 of their papers we have counts for
3 papers
Multivariate Analysis on Performance Gaps of Artificial Intelligence Models in Screening Mammography
Linglin Zhang, Beatrice Brown-Mulry, Vineela Nalla +7
Although deep learning models for abnormality classification can perform well in screening mammography, the demographic, imaging, and clinical characteristics associated with incre…
GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging
Sarthak Pati, Siddhesh P. Thakur, İbrahim Ethem Hamamcı +39
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities. However, greater expertise is required to develop DL algorithms,…
Deep-LIBRA: Artificial intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment
Omid Haji Maghsoudi, Aimilia Gastounioti, Christopher Scott +7
Breast density is an important risk factor for breast cancer that also affects the specificity and sensitivity of screening mammography. Current federal legislation mandates report…