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10/27/2020
On the diminishing return of labeling clinical reports
Ample evidence suggests that better machine learning models may be stead...
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10/01/2019
Learning to estimate label uncertainty for automatic radiology report parsing
Bootstrapping labels from radiology reports has become the scalable alte...
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05/06/2019
Caveats in Generating Medical Imaging Labels from Radiology Reports
Acquiring high-quality annotations in medical imaging is usually a costl...
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04/02/2019
A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging
This work provides a strong baseline for the problem of multi-source mul...
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10/01/2018
Efficient and Accurate Abnormality Mining from Radiology Reports with Customized False Positive Reduction
Obtaining datasets labeled to facilitate model development is a challeng...
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03/21/2018
Weakly Supervised Medical Diagnosis and Localization from Multiple Resolutions
Diagnostic imaging often requires the simultaneous identification of a m...
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10/28/2017
Learning to diagnose from scratch by exploiting dependencies among labels
The field of medical diagnostics contains a wealth of challenges which c...
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05/09/2016
Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate...
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11/19/2015
Delving Deeper into Convolutional Networks for Learning Video Representations
We propose an approach to learn spatio-temporal features in videos from ...
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11/14/2015
Oracle performance for visual captioning
The task of associating images and videos with a natural language descri...
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03/18/2015
GSNs : Generative Stochastic Networks
We introduce a novel training principle for probabilistic models that is...
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02/27/2015
Describing Videos by Exploiting Temporal Structure
Recent progress in using recurrent neural networks (RNNs) for image desc...
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12/19/2013
Multimodal Transitions for Generative Stochastic Networks
Generative Stochastic Networks (GSNs) have been recently introduced as a...
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05/29/2013