The machine-learning model could help scientists speed the development of new medicines.

Scientists demonstrate that AI-risk models, paired with AI-designed screening policies, can offer significant and equitable improvements to cancer screening.

To help clinicians avoid remedies that may potentially contribute to a patient’s death, researchers at MIT and elsewhere have developed a machine-learning model that could be used to identify treatments that pose a higher risk than other options.

A deep learning model rapidly predicts the 3D shapes of drug-like molecules, which could accelerate the process of discovering new medicines.

Alumnus-founded Fitnescity makes it easier for users to schedule health tests, work with physicians, and interpret results.

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.

MIT researchers employ machine learning to find powerful peptides that could improve a gene therapy drug for Duchenne muscular dystrophy.

CSAIL created a new method to computationally optimize the shape and control of a robotic manipulator for a specific task.

MIT engineers design the first synthetic circuit that consists entirely of fast, reversible protein-protein interactions.