Tag: Machine Learning
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Machine learning begins to understand the human gut
The new computer model accurately predicts the behavior of millions of microbial communities from hundreds of experiments, an advance toward precision medicine.
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Update: Augmented reality engineering startup lands $1.1M SBIR grant
University of Michigan to explore inventive uses for the technology, including material science, biology and medicine
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Immune to hacks: Inoculating deep neural networks to thwart attacks
The adaptive immune system serves as a template for defending neural nets from confusion-sowing attacks.
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Open-source patient model tops industry standard
Tested without needing hospitals to share data, the method for developing the model could speed further improvements in medical prediction tools.
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Calculating the best shapes for things to come
A new algorithm efficiently determines optimal shapes for structures.
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Augmented reality for testing nuclear components
A new machine learning platform detects and quantifies radiation-induced defects instantaneously and could be extended to interpret other microscopy data.
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Individual finger control for advanced prostheses demonstrated in primates
An electrode array implanted in the brain predicts finger motions in near real time.
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“Robot assistants” project aims to reinvent construction industry
$2M project aims to partner humans with robots for safer jobsites.
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Machine learning links material composition and performance in catalysts
Understanding how to design better catalysts could enable sustainable energy tech and make everyday chemicals more environmentally friendly.
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Live public street cams are tracking social distancing
Virtually visit (what should be) desolate intersections around the world during COVID-19.
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Could a smartwatch identify an infection before you start spreading it?
A wrist-worn device detected disrupted sleep 24 hours before study participants began shedding flu viruses.
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Preventing deadly hospital infections with machine learning
Model successfully applied to data from medical centers with different patient populations, electronic health record systems