Using AI and old reports to understand new medical images
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
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Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
Neural network identifies synergistic drug blends for treating viruses like SARS-CoV-2.
An AI-enhanced system enables doctors to spend less time searching for clinical information and more time treating patients.
An electrical impedance tomography toolkit lets users design and fabricate health and motion sensing devices.
MIT scientists show how fast algorithms are improving across a broad range of examples, demonstrating their critical importance in advancing computing.
MIT professors Dave Des Marais and Caroline Uhler combine plant biology and machine learning to identify genetic roots of plant responses to environmental stress.
The MIT School of Engineering honors excellence in teaching and advising, as well as academic achievement.
Advance incorporates sensing directly into an object’s material, with applications for assistive technology and “intelligent” furniture.
New chip eliminates the need for specific decoding hardware, could boost efficiency of gaming systems, 5G networks, the internet of things, and more.
Record number of honorees will engage in the life of the Institute through teaching, research, and other interactions with the MIT community.
MIT professor is designing the next generation of smart wireless devices that will sit in the background, gathering and interpreting data, rather than being worn on the body.
A former department head who established the MEng degree for EECS undergraduates, Penfield developed courses illuminating the equivalence of information and thermodynamic entropy.
This year’s projects address mobile evaporative vegetable preservation, portable water filtration, and dairy waste reduction.
For the past seven years, the MIT University Center for Exemplary Mentoring has created a robust infrastructure of resources, people, and support.
MIT researchers find a new way to quantify the uncertainty in molecular energies predicted by neural networks.