11 citations · 23 across the 11 of their papers we have counts for
6 papers · 1 filter
STA-Risk: A Deep Dive of Spatio-Temporal Asymmetries for Breast Cancer Risk Prediction
Zhengbo Zhou, Dooman Arefan, Margarita Zuley +2
Predicting the risk of developing breast cancer is an important clinical tool to guide early intervention and tailoring personalized screening strategies. Early risk models have li…
Adversarially Robust Feature Learning for Breast Cancer Diagnosis
Degan Hao, Dooman Arefan, Margarita Zuley +2
Adversarial data can lead to malfunction of deep learning applications. It is essential to develop deep learning models that are robust to adversarial data while accurate on standa…
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification
Long Gao, Chang Liu, Dooman Arefan +3
Deep learning models have gained remarkable performance on a variety of image classification tasks. However, many models suffer from limited performance in clinical or medical sett…
Constrained Deep One-Class Feature Learning For Classifying Imbalanced Medical Images
Long Gao, Chang Liu, Dooman Arefan +2
Medical image data are usually imbalanced across different classes. One-class classification has attracted increasing attention to address the data imbalance problem by distinguish…
Knowledge-Guided Multiview Deep Curriculum Learning for Elbow Fracture Classification
Jun Luo, Gene Kitamura, Dooman Arefan +3
Elbow fracture diagnosis often requires patients to take both frontal and lateral views of elbow X-ray radiographs. In this paper, we propose a multiview deep learning method for a…
Medical Knowledge-Guided Deep Curriculum Learning for Elbow Fracture Diagnosis from X-Ray Images
Jun Luo, Gene Kitamura, Emine Doganay +2
Elbow fractures are one of the most common fracture types. Diagnoses on elbow fractures often need the help of radiographic imaging to be read and analyzed by a specialized radiolo…