9 citations · 17 across the 8 of their papers we have counts for
8 papers
From 2D to 3D Without Extra Baggage: Data-Efficient Cancer Detection in Digital Breast Tomosynthesis
Yen Nhi Truong Vu, Dan Guo, Sripad Joshi +3
Digital Breast Tomosynthesis (DBT) enhances finding visibility for breast cancer detection by providing volumetric information that reduces the impact of overlapping tissues; howev…
M&M: Tackling False Positives in Mammography with a Multi-view and Multi-instance Learning Sparse Detector
Yen Nhi Truong Vu, Dan Guo, Ahmed Taha +2
Deep-learning-based object detection methods show promise for improving screening mammography, but high rates of false positives can hinder their effectiveness in clinical practice…
Problems and shortcuts in deep learning for screening mammography
Trevor Tsue, Brent Mombourquette, Ahmed Taha +3
This work reveals undiscovered challenges in the performance and generalizability of deep learning models. We (1) identify spurious shortcuts and evaluation issues that can inflate…
Deep is a Luxury We Don't Have
Ahmed Taha, Yen Nhi Truong Vu, Brent Mombourquette +3
Medical images come in high resolutions. A high resolution is vital for finding malignant tissues at an early stage. Yet, this resolution presents a challenge in terms of modeling…
A deep learning algorithm for reducing false positives in screening mammography
Stefano Pedemonte, Trevor Tsue, Brent Mombourquette +10
Screening mammography improves breast cancer outcomes by enabling early detection and treatment. However, false positive callbacks for additional imaging from screening exams cause…
On algorithms to calculate integer complexity
Katherine Cordwell, Alyssa Epstein, Anand Hemmady +5
We consider a problem first proposed by Mahler and Popken in 1953 and later developed by Coppersmith, Erdős, Guy, Isbell, Selfridge, and others. Let be the complexity of $n…
Random Matrix Ensembles with Split Limiting Behavior
Paula Burkhardt, Peter Cohen, Jonathan Dewitt +6
We introduce a new family of random real symmetric matrix ensembles, the -checkerboard matrices, whose limiting spectral measure has two components which can be dete…
Summand minimality and asymptotic convergence of generalized Zeckendorf decompositions
Katherine Cordwell, Max Hlavacek, Chi Huynh +3
Given a recurrence sequence , with where for all and , the generalized Zeckendorf decomposi…