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10/16/2022
3D-GMIC: an efficient deep neural network to find small objects in large 3D images
3D imaging enables a more accurate diagnosis by providing spatial inform...
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07/14/2022
MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images
Multi-modal fusion approaches aim to integrate information from differen...
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02/10/2022
Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks
We hypothesize that due to the greedy nature of learning in multi-modal ...
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11/04/2021
Towards dynamic multi-modal phenotyping using chest radiographs and physiological data
The healthcare domain is characterized by heterogeneous data modalities,...
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08/10/2021
Meta-repository of screening mammography classifiers
Artificial intelligence (AI) is transforming medicine and showing promis...
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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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01/13/2021
COVID-19 Deterioration Prediction via Self-Supervised Representation Learning and Multi-Image Prediction
The rapid spread of COVID-19 cases in recent months has strained hospita...
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11/28/2020
Differences between human and machine perception in medical diagnosis
Deep neural networks (DNNs) show promise in image-based medical diagnosi...
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10/19/2020
Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability
Saliency maps that identify the most informative regions of an image for...
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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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03/23/2020
Understanding the robustness of deep neural network classifiers for breast cancer screening
Deep neural networks (DNNs) show promise in breast cancer screening, but...
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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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08/01/2019
Improving localization-based approaches for breast cancer screening exam classification
We trained and evaluated a localization-based deep CNN for breast cancer...
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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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11/21/2018
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measuremen...
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05/21/2018
Classifier-agnostic saliency map extraction
We argue for the importance of decoupling saliency map extraction from a...
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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
High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks
Recent advances in deep learning for natural images has prompted a surge...
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03/17/2016
