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National Institutes of Health (NIH)

The new system pinpoints medications that should not be combined.

Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed a system using tissue models and machine-learning algorithms to identify how different drugs navigate through the lining of the digestive tract, which could have significant implications for the world of medicine. Orally-taken drugs often rely on transporter proteins within the digestive tract's cells to…

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The latest model pinpoints medications that should not be combined.

American researchers at MIT, Brigham and Women’s Hospital, and Duke University have designed an innovative approach to identifying the transporters used by different drugs that are taken orally. The strategy involves the use of both tissue models and machine-learning algorithms, and has already revealed that a commonly prescribed antibiotic and a blood thinner can interfere…

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There is potential in deep neural networks as they could effectively serve as models for human auditory perception.

A new MIT study has found that computational models derived from machine learning that mimic the structure and function of the human auditory system could help improve the design of hearing aids, cochlear implants, and brain-machine interfaces. Its research explored deep neural networks trained to perform auditory tasks and showed that these models generate internal…

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Bridging the gap between design and production for optical instruments.

Photolithography, the technique used to create computer chips and optical devices, often results in minuscule deviations from design intentions. With the goal of closing the gap between design and manufacturing, a team of researchers from MIT and the Chinese University of Hong Kong, led by mechanical engineering graduate student Cheng Zheng, used machine learning to…

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Bridging the divide between design and production for optical instruments

Photolithography is a crucial process in the manufacturing of computer chips and other optical devices, but validity between the design and the final product often falls short due to tiny variations in the manufacturing process. To address this issue, researchers from MIT and the Chinese University of Hong Kong have developed a machine-learning aided digital…

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The potential of deep neural networks as models for human auditory perception is quite promising.

A recent study from MIT has shown that computational models that mimic the structure and function of the human auditory system could significantly aid research into more sophisticated hearing aids, cochlear implants, and brain-machine interfaces. Modern computational models that use machine learning have already made progress in this area. The MIT team carried out the…

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Bridging the gap between design and production for optical instruments.

Photolithography, a process used to fabricate computer chips and optical devices, often falls short of designers' intentions due to tiny deviations during manufacturing. To address this, researchers from MIT and the Chinese University of Hong Kong have used machine learning to develop a digital simulator that precisely replicates a specific photolithography manufacturing process. The simulator…

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Deep neural networks demonstrate potential in simulating human auditory perception.

A new study from MIT reveals that modern computational models based on machine learning, which mimic the structure and function of the human auditory system, are coming closer to potentially aiding the design of improved hearing aids, cochlear implants, and brain-machine interfaces. The MIT team’s research is the most extensive to date on deep neural networks,…

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Bridging the gap between designing and manufacturing in the field of optical devices.

Photolithography, a process used to create computer chips and optical devices, can often have tiny deviations during production, causing the final product to fall short of the initial design. To address this, researchers from MIT and the Chinese University of Hong Kong have used machine learning to develop a digital simulator that more accurately models…

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Deep neural networks exhibit potential for modelling human auditory processes.

A new study from MIT suggests that modern computational models powered by machine learning could potentially aid the design of better hearing aids, cochlear implants, and brain-machine interfaces. These models, specifically deep neural networks, are starting to encompass functions that replicate the structure of the human auditory system.  The study further illuminates how to best train…

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