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There's an obvious problem with applying deep learning to language.
At Stanford, I worked on applying deep learning methods to relation extraction and knowledge base population.
There is an increasing interest in applying deep learning to 3D mesh segmentation.
Jointly with Lehman and graduate student Nicolas Locascio, Barzilay is applying deep learning for automating analysis of mammogram data.
We propose to address this challenging problem by investigating the potential of applying deep learning techniques to this field.
Language remains a very tricky problem for artificial intelligence, but in recent years researchers have made progress in applying deep learning to the problem (see "AI's Language Problem").
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It's not the first attempt to apply deep learning to health care.
Nvidia is, for example, working with Bradley Erickson, a neuro-radiologist at the Mayo Clinic, to apply deep learning to brain images.
EECS alumnus Bryan Catanzaro, Ph.D. '11 (advisor Prof. Kurt Keutzer) has joined NVIDIA as the Vice President of applied deep learning research.
Among publicly available systems, the best is probably a Stanford project, called Deeply Moving, that applies deep learning to the task of understanding movie reviews.
DeepMind has since gone on to apply deep learning in a range of situations, most famously to outperform humans in the ancient game of Go.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com