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AI Speeds Nanoparticle Development Through Light Scattering Prediction

News   Jun 11, 2018 | Original Press Release by David L. Chandler for MIT

AI Speeds Nanoparticle Development

This cloaking grenade, used for hiding troop operations from view on the battlefield, is an example of nanoparticles that reflect a particular color of light based on their exact size and composition. New work by MIT researchers provides a way to predict the light-scattering properties of layered nanoparticles – or to design particles to match a desired type of light-scattering behavior. Credit: Wikipedia



Electronic Medical Records Show Promise in Reducing Unnecessary Testing


Upon implementing electronic medical record-based interventions, Boston Medical Center reduced unnecessary diagnostic testing and increased the use of postoperative order sets, two markers of providing high-value medical care.


The Building Blocks of an Electronic Brain


Computer bits are binary, with a value of 0 or 1. By contrast, neurons in the brain can have all kinds of different internal states, depending on the input that they received. This allows the brain to process information in a more energy-efficient manner than a computer. A new study hopes to bring the two closer together.


Cryptographic Protocol Enables Greater Collaboration in Drug Discovery


MIT researchers have developed a cryptographic system that could help neural networks identify promising drug candidates in massive pharmacological datasets, while keeping the data private. Secure computation done at such a massive scale could enable broad pooling of sensitive pharmacological data for predictive drug discovery.



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