Joseph Paul Cohen

research

∙ 04/02/2023

The Effect of Counterfactuals on Reading Chest X-rays

This study evaluates the effect of counterfactual explanations on the in...

0 Joseph Paul Cohen, et al. ∙

research

∙ 12/27/2021

Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models

Learning models that generalize under different distribution shifts in m...

13 Enoch Tetteh, et al. ∙

research

∙ 10/31/2021

TorchXRayVision: A library of chest X-ray datasets and models

TorchXRayVision is an open source software library for working with ches...

0 Joseph Paul Cohen, et al. ∙

research

∙ 02/18/2021

Benefits of Linear Conditioning for Segmentation using Metadata

Medical images are often accompanied by metadata describing the image (v...

0 Andréanne Lemay, et al. ∙

research

∙ 02/18/2021

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays

Motivation: Traditional image attribution methods struggle to satisfacto...

10 Joseph Paul Cohen, et al. ∙

research

∙ 10/20/2020

ivadomed: A Medical Imaging Deep Learning Toolbox

ivadomed is an open-source Python package for designing, end-to-end trai...

0 Charley Gros, et al. ∙

research

∙ 09/17/2020

S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning

Deep Metric Learning (DML) provides a crucial tool for visual similarity...

16 Karsten Roth, et al. ∙

research

∙ 07/26/2020

Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Prediction

A common approach to medical image analysis on volumetric data uses deep...

23 Hasib Zunair, et al. ∙

research

∙ 07/08/2020

A Benchmark of Medical Out of Distribution Detection

There is a rise in the use of deep learning for automated medical diagno...

50 Tianshi Cao, et al. ∙

research

∙ 06/22/2020

COVID-19 Image Data Collection: Prospective Predictions Are the Future

Across the world's coronavirus disease 2019 (COVID-19) hot spots, the ne...

11 Joseph Paul Cohen, et al. ∙

research

∙ 05/24/2020

Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning

The need to streamline patient management for COVID-19 has become more p...

0 Joseph Paul Cohen, et al. ∙

research

∙ 04/28/2020

DiVA: Diverse Visual Feature Aggregation forDeep Metric Learning

Visual Similarity plays an important role in many computer vision applic...

3 Timo Milbich, et al. ∙

research

∙ 04/28/2020

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning

Visual Similarity plays an important role in many computer vision applic...

0 Timo Milbich, et al. ∙

research

∙ 03/25/2020

COVID-19 Image Data Collection

This paper describes the initial COVID-19 open image data collection. It...

163 Joseph Paul Cohen, et al. ∙

research

∙ 03/09/2020

Spine intervertebral disc labeling using a fully convolutional redundant counting model

Labeling intervertebral discs is relevant as it notably enables clinicia...

0 Lucas Rouhier, et al. ∙

research

∙ 03/09/2020

Automatic segmentation of spinal multiple sclerosis lesions: How to generalize across MRI contrasts?

Despite recent improvements in medical image segmentation, the ability t...

0 Olivier Vincent, et al. ∙

research

∙ 02/19/2020

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning

Deep Metric Learning (DML) is arguably one of the most influential lines...

0 Karsten Roth, et al. ∙

research

∙ 02/07/2020

Quantifying the Value of Lateral Views in Deep Learning for Chest X-rays

Most deep learning models in chest X-ray prediction utilize the posteroa...

0 Mohammad Hashir, et al. ∙

research

∙ 02/06/2020

On the limits of cross-domain generalization in automated X-ray prediction

This large scale study focuses on quantifying what X-rays diagnostic pre...

0 Joseph Paul Cohen, et al. ∙

research

∙ 10/21/2019

Is graph biased feature selection of genes better than random?

Gene interaction graphs aim to capture various relationships between gen...

0 Mohammad Hashir, et al. ∙

research

∙ 10/21/2019

Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery

We release the largest public ECG dataset of continuous raw signals for ...

12 Shawn Tan, et al. ∙

research

∙ 10/18/2019

The TCGA Meta-Dataset Clinical Benchmark

Machine learning is bringing a paradigm shift to healthcare by changing ...

9 Mandana Samiei, et al. ∙

research

∙ 10/16/2019

Deep Semantic Segmentation of Natural and Medical Images: A Review

The (medical) image semantic segmentation task consists of classifying e...

0 Saed Asgari Taghanaki, et al. ∙

research

∙ 10/01/2019

Underwhelming Generalization Improvements From Controlling Feature Attribution

Overfitting is a common issue in machine learning, which can arise when ...

25 Joseph D. Viviano, et al. ∙

research

∙ 09/14/2019

Torchmeta: A Meta-Learning library for PyTorch

The constant introduction of standardized benchmarks in the literature h...

20 Tristan Deleu, et al. ∙

research

∙ 05/06/2019

Analysis of Gene Interaction Graphs for Biasing Machine Learning Models

Gene interaction graphs aim to capture various relationships between gen...

0 Paul Bertin, et al. ∙

research

∙ 04/17/2019

Do Lateral Views Help Automated Chest X-ray Predictions?

Most convolutional neural networks in chest radiology use only the front...

0 Hadrien Bertrand, et al. ∙

research

∙ 04/16/2019

GradMask: Reduce Overfitting by Regularizing Saliency

With too few samples or too many model parameters, overfitting can inhib...

0 Becks Simpson, et al. ∙

research

∙ 01/31/2019

Chester: A Web Delivered Locally Computed Chest X-Ray Disease Prediction System

Deep learning has shown promise to augment radiologists and improve the ...

0 Joseph Paul Cohen, et al. ∙

research

∙ 10/08/2018

Towards the Latent Transcriptome

In this work we propose a method to compute continuous embeddings for km...

0 Assya Trofimov, et al. ∙

research

∙ 06/18/2018

Towards Gene Expression Convolutions using Gene Interaction Graphs

We study the challenges of applying deep learning to gene expression dat...

0 Francis Dutil, et al. ∙

research

∙ 06/06/2018

Learning to rank for censored survival data

Survival analysis is a type of semi-supervised ranking task where the ta...

0 Margaux Luck, et al. ∙

research

∙ 05/22/2018

Distribution Matching Losses Can Hallucinate Features in Medical Image Translation

This paper discusses how distribution matching losses, such as those use...

0 Joseph Paul Cohen, et al. ∙

research

∙ 12/12/2017

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models

Directed latent variable models that formulate the joint distribution as...

0 Alex Lamb, et al. ∙

research

∙ 07/20/2017

ShortScience.org - Reproducing Intuition

We present ShortScience.org, a platform for post-publication discussion ...

0 Joseph Paul Cohen, et al. ∙

research

∙ 03/25/2017

Count-ception: Counting by Fully Convolutional Redundant Counting

Counting objects in digital images is a process that should be replaced ...

0 Joseph Paul Cohen, et al. ∙

research

∙ 03/14/2016

Rapid building detection using machine learning

This work describes algorithms for performing discrete object detection,...

0 Joseph Paul Cohen, et al. ∙

research

∙ 02/18/2016

RandomOut: Using a convolutional gradient norm to rescue convolutional filters

Filters in convolutional neural networks are sensitive to their initiali...

0 Joseph Paul Cohen, et al. ∙

research

∙ 01/05/2016

Crater Detection via Convolutional Neural Networks

Craters are among the most studied geomorphic features in the Solar Syst...

0 Joseph Paul Cohen, et al. ∙

Joseph Paul Cohen

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