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11/13/2021
Minimax Supervised Clustering in the Anisotropic Gaussian Mixture Model: A new take on Robust Interpolation
We study the supervised clustering problem under the two-component aniso...
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10/07/2021
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations
Deep learning in the presence of noisy annotations has been studied exte...
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06/13/2021
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis
In the last few years, deep learning classifiers have shown promising re...
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09/19/2020
Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms
Breast cancer is the most common cancer in women, and hundreds of thousa...
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08/04/2020
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department
During the COVID-19 pandemic, rapid and accurate triage of patients at t...
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02/13/2020
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
Medical images differ from natural images in significantly higher resolu...
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07/30/2019
Screening Mammogram Classification with Prior Exams
Radiologists typically compare a patient's most recent breast cancer scr...
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06/07/2019
Globally-Aware Multiple Instance Classifier for Breast Cancer Screening
Deep learning models designed for visual classification tasks on natural...
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03/20/2019
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
We present a deep convolutional neural network for breast cancer screeni...
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11/10/2017
Breast density classification with deep convolutional neural networks
Breast density classification is an essential part of breast cancer scre...
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03/21/2017
