no code implementations • 22 Jan 2024 • Zhihong Chen, Maya Varma, Jean-Benoit Delbrouck, Magdalini Paschali, Louis Blankemeier, Dave Van Veen, Jeya Maria Jose Valanarasu, Alaa Youssef, Joseph Paul Cohen, Eduardo Pontes Reis, Emily B. Tsai, Andrew Johnston, Cameron Olsen, Tanishq Mathew Abraham, Sergios Gatidis, Akshay S. Chaudhari, Curtis Langlotz
However, developing FMs that can accurately interpret CXRs is challenging due to the (1) limited availability of large-scale vision-language datasets in the medical image domain, (2) lack of vision and language encoders that can capture the complexities of medical data, and (3) absence of evaluation frameworks for benchmarking the abilities of FMs on CXR interpretation.
1 code implementation • 1 Dec 2023 • Joseph Paul Cohen, Louis Blankemeier, Akshay Chaudhari
We propose the counterfactual alignment method to detect and explore spurious correlations of black box classifiers.
1 code implementation • 2 Apr 2023 • Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew Lungren, Akshay Chaudhari
This study evaluates the effect of counterfactual explanations on the interpretation of chest X-rays.
1 code implementation • 27 Nov 2022 • Reza Azad, Ehsan Khodapanah Aghdam, Amelie Rauland, Yiwei Jia, Atlas Haddadi Avval, Afshin Bozorgpour, Sanaz Karimijafarbigloo, Joseph Paul Cohen, Ehsan Adeli, Dorit Merhof
U-Net is the most widespread image segmentation architecture due to its flexibility, optimized modular design, and success in all medical image modalities.
1 code implementation • 6 Feb 2022 • Arjun Soin, Jameson Merkow, Jin Long, Joseph Paul Cohen, Smitha Saligrama, Stephen Kaiser, Steven Borg, Ivan Tarapov, Matthew P Lungren
We use the CheXpert and PadChest public datasets to build and test a medical imaging AI drift monitoring workflow to track data and model drift without contemporaneous ground truth.
1 code implementation • 27 Dec 2021 • Enoch Tetteh, Joseph Viviano, Yoshua Bengio, David Krueger, Joseph Paul Cohen
Learning models that generalize under different distribution shifts in medical imaging has been a long-standing research challenge.
1 code implementation • 31 Oct 2021 • Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin, Paul Morrison, Parsa Torabian, Matteo Guarrera, Matthew P Lungren, Akshay Chaudhari, Rupert Brooks, Mohammad Hashir, Hadrien Bertrand
TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models.
1 code implementation • Proceedings of Machine Learning Research 1:1–13 2021 • Margaux Luck*, Tristan Sylvain*, Joseph Paul Cohen, Heloise Cardinal, Andrea Lodi, Yoshua Bengio
Survival analysis is a type of semi-supervised task where the target output (the survival time) is often right-censored.
no code implementations • 18 Feb 2021 • Andreanne Lemay, Charley Gros, Olivier Vincent, Yaou Liu, Joseph Paul Cohen, Julien Cohen-Adad
This metadata is usually disregarded by image segmentation methods.
2 code implementations • 18 Feb 2021 • Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew P. Lungren, Akshay Chaudhari
We also found that the Latent Shift explanation allows a user to have more confidence in true positive predictions compared to traditional approaches (0. 15$\pm$0. 95 in a 5 point scale with p=0. 01) with only a small increase in false positive predictions (0. 04$\pm$1. 06 with p=0. 57).
1 code implementation • 20 Oct 2020 • Charley Gros, Andreanne Lemay, Olivier Vincent, Lucas Rouhier, Anthime Bucquet, Joseph Paul Cohen, Julien Cohen-Adad
ivadomed is an open-source Python package for designing, end-to-end training, and evaluating deep learning models applied to medical imaging data.
1 code implementation • 17 Sep 2020 • Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
Deep Metric Learning (DML) provides a crucial tool for visual similarity and zero-shot applications by learning generalizing embedding spaces, although recent work in DML has shown strong performance saturation across training objectives.
Ranked #10 on Metric Learning on CARS196 (using extra training data)
3 code implementations • 26 Jul 2020 • Hasib Zunair, Aimon Rahman, Nabeel Mohammed, Joseph Paul Cohen
A common approach to medical image analysis on volumetric data uses deep 2D convolutional neural networks (CNNs).
3 code implementations • 8 Jul 2020 • Tianshi Cao, Chin-wei Huang, David Yu-Tung Hui, Joseph Paul Cohen
However it is unclear which OoDD method should be used in practice.
6 code implementations • 22 Jun 2020 • Joseph Paul Cohen, Paul Morrison, Lan Dao, Karsten Roth, Tim Q Duong, Marzyeh Ghassemi
This dataset currently contains hundreds of frontal view X-rays and is the largest public resource for COVID-19 image and prognostic data, making it a necessary resource to develop and evaluate tools to aid in the treatment of COVID-19.
6 code implementations • 24 May 2020 • Joseph Paul Cohen, Lan Dao, Paul Morrison, Karsten Roth, Yoshua Bengio, Beiyi Shen, Almas Abbasi, Mahsa Hoshmand-Kochi, Marzyeh Ghassemi, Haifang Li, Tim Q Duong
In this study, we present a severity score prediction model for COVID-19 pneumonia for frontal chest X-ray images.
2 code implementations • ECCV 2020 • Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen
Visual Similarity plays an important role in many computer vision applications.
Ranked #13 on Metric Learning on CUB-200-2011 (using extra training data)
13 code implementations • 25 Mar 2020 • Joseph Paul Cohen, Paul Morrison, Lan Dao
This paper describes the initial COVID-19 open image data collection.
1 code implementation • 9 Mar 2020 • Olivier Vincent, Charley Gros, Joseph Paul Cohen, Julien Cohen-Adad
Despite recent improvements in medical image segmentation, the ability to generalize across imaging contrasts remains an open issue.
1 code implementation • MIDL 2019 • Lucas Rouhier, Francisco Perdigon Romero, Joseph Paul Cohen, Julien Cohen-Adad
Labeling intervertebral discs is relevant as it notably enables clinicians to understand the relationship between a patient's symptoms (pain, paralysis) and the exact level of spinal cord injury.
8 code implementations • ICML 2020 • Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen
Deep Metric Learning (DML) is arguably one of the most influential lines of research for learning visual similarities with many proposed approaches every year.
1 code implementation • MIDL 2019 • Mohammad Hashir, Hadrien Bertrand, Joseph Paul Cohen
PadChest is a large-scale chest X-ray dataset that has almost 200 labels and multiple views available.
9 code implementations • MIDL 2019 • Joseph Paul Cohen, Mohammad Hashir, Rupert Brooks, Hadrien Bertrand
This large scale study focuses on quantifying what X-rays diagnostic prediction tasks generalize well across multiple different datasets.
no code implementations • MIDL 2019 • Tianshi Cao, David Yu-Tung Hui, Chinwei Huang, Joseph Paul Cohen
There is a rise in the use of deep learning for automated medical diagnosis, most notably in medical imaging.
1 code implementation • 21 Oct 2019 • Mohammad Hashir, Paul Bertin, Martin Weiss, Vincent Frappier, Theodore J. Perkins, Geneviève Boucher, Joseph Paul Cohen
Gene interaction graphs aim to capture various relationships between genes and represent decades of biology research.
1 code implementation • 21 Oct 2019 • Shawn Tan, Guillaume Androz, Ahmad Chamseddine, Pierre Fecteau, Aaron Courville, Yoshua Bengio, Joseph Paul Cohen
We release the largest public ECG dataset of continuous raw signals for representation learning containing 11 thousand patients and 2 billion labelled beats.
1 code implementation • 18 Oct 2019 • Mandana Samiei, Tobias Würfl, Tristan Deleu, Martin Weiss, Francis Dutil, Thomas Fevens, Geneviève Boucher, Sebastien Lemieux, Joseph Paul Cohen
Machine learning is bringing a paradigm shift to healthcare by changing the process of disease diagnosis and prognosis in clinics and hospitals.
no code implementations • 16 Oct 2019 • Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen, Julien Cohen-Adad, Ghassan Hamarneh
The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class.
1 code implementation • ICLR 2021 • Joseph D. Viviano, Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen
In some prediction tasks, such as for medical images, one may have some images with masks drawn by a human expert, indicating a region of the image containing relevant information to make the prediction.
no code implementations • 25 Sep 2019 • Joseph D Viviano, Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen
We describe a simple method for taking advantage of such auxiliary labels, by training networks to ignore the distracting features which may be extracted outside of the region of interest, on the training images for which such masks are available.
no code implementations • 25 Sep 2019 • Mohammad Hashir, Yoshua Bengio, Joseph Paul Cohen
The validation curve is widely used for model selection and hyper-parameter search with the curve usually summarized over all the training tasks.
no code implementations • 25 Sep 2019 • Shawn Tan, Guillaume Androz, Ahmad Chamseddine, Pierre Fecteau, Aaron Courville, Yoshua Bengio, Joseph Paul Cohen
We release the largest public ECG dataset of continuous raw signals for representation learning containing over 11k patients and 2 billion labelled beats.
5 code implementations • 14 Sep 2019 • Tristan Deleu, Tobias Würfl, Mandana Samiei, Joseph Paul Cohen, Yoshua Bengio
The constant introduction of standardized benchmarks in the literature has helped accelerating the recent advances in meta-learning research.
1 code implementation • 6 May 2019 • Paul Bertin, Mohammad Hashir, Martin Weiss, Vincent Frappier, Theodore J. Perkins, Geneviève Boucher, Joseph Paul Cohen
Gene interaction graphs aim to capture various relationships between genes and can represent decades of biology research.
1 code implementation • 17 Apr 2019 • Hadrien Bertrand, Mohammad Hashir, Joseph Paul Cohen
Most convolutional neural networks in chest radiology use only the frontal posteroanterior (PA) view to make a prediction.
no code implementations • 16 Apr 2019 • Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen
With too few samples or too many model parameters, overfitting can inhibit the ability to generalise predictions to new data.
1 code implementation • MIDL 2019 • Joseph Paul Cohen, Paul Bertin, Vincent Frappier
In order to bridge the gap between Deep Learning researchers and medical professionals we develop a very accessible free prototype system which can be used by medical professionals to understand the reality of Deep Learning tools for chest X-ray diagnostics.
no code implementations • 25 Nov 2018 • Martin Weiss, Margaux Luck, Roger Girgis, Chris Pal, Joseph Paul Cohen
The number of visually impaired or blind (VIB) people in the world is estimated at several hundred million.
1 code implementation • 8 Oct 2018 • Assya Trofimov, Francis Dutil, Claude Perreault, Sebastien Lemieux, Yoshua Bengio, Joseph Paul Cohen
In this work we propose a method to compute continuous embeddings for kmers from raw RNA-seq data, without the need for alignment to a reference genome.
1 code implementation • 18 Jun 2018 • Francis Dutil, Joseph Paul Cohen, Martin Weiss, Georgy Derevyanko, Yoshua Bengio
We find this approach provides an advantage for particular tasks in a low data regime but is very dependent on the quality of the graph used.
1 code implementation • 6 Jun 2018 • Margaux Luck, Tristan Sylvain, Joseph Paul Cohen, Heloise Cardinal, Andrea Lodi, Yoshua Bengio
Survival analysis is a type of semi-supervised ranking task where the target output (the survival time) is often right-censored.
1 code implementation • 22 May 2018 • Joseph Paul Cohen, Margaux Luck, Sina Honari
When the output of an algorithm is a transformed image there are uncertainties whether all known and unknown class labels have been preserved or changed.
no code implementations • NeurIPS 2017 • Alex Lamb, Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron Courville, Yoshua Bengio
Directed latent variable models that formulate the joint distribution as $p(x, z) = p(z) p(x \mid z)$ have the advantage of fast and exact sampling.
1 code implementation • 20 Jul 2017 • Joseph Paul Cohen, Henry Z. Lo
We present ShortScience. org, a platform for post-publication discussion of research papers.
Digital Libraries
2 code implementations • 25 Mar 2017 • Joseph Paul Cohen, Genevieve Boucher, Craig A. Glastonbury, Henry Z. Lo, Yoshua Bengio
Our contribution is redundant counting instead of predicting a density map in order to average over errors.
no code implementations • 14 Mar 2016 • Joseph Paul Cohen, Wei Ding, Caitlin Kuhlman, Aijun Chen, Liping Di
This work describes algorithms for performing discrete object detection, specifically in the case of buildings, where usually only low quality RGB-only geospatial reflective imagery is available.
1 code implementation • 18 Feb 2016 • Joseph Paul Cohen, Henry Z. Lo, Wei Ding
We propose to evaluate and replace specific convolutional filters that have little impact on the prediction.
1 code implementation • 5 Jan 2016 • Joseph Paul Cohen, Henry Z. Lo, Ting-ting Lu, Wei Ding
The power of CNNs is that they can learn image filters which generate features for high accuracy classification.
1 code implementation • 6 May 2015 • Joseph Paul Cohen, Wei Ding, Abraham Bagherjeiran
We propose the XTreePath annotation method to captures contextual node information from the training DOM.