MIT researchers performed a large-scale, high resolution study of the cells in human breast milk, allowing them to track how these cells change over time in nursing mothers.

A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.

Researchers from MIT have created a comprehensive atlas of the types of cells found in the brain cerebrovasculature.

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.