Our goal is to develop AI technologies that will change the landscape of healthcare and the life sciences. This includes the whole span from the discovery of biological mechanisms to early disease diagnostics, drug discovery, care personalization and management. Building on MIT’s pioneering history in artificial intelligence and life sciences, we are working on algorithms suitable for modeling biological and clinical data across a range of modalities including imaging, text and genomics.
While achieving this goal, we strive to make new discoveries in machine learning, biology, chemistry and clinical sciences, and translate our discoveries into technologies that can improve people’s lives. While the Jameel Clinic focuses primarily on AI and Health, other research labs and centers affiliated with EECS have groups engaged in AI for healthcare and life sciences, including IMES, CSAIL, LIDS, and the Eric and Wendy Schmidt Center at the Broad Institute.
Latest news in AI for healthcare and life sciences
BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.
Co-founded by an EECS alumnus, Watershed Bio offers researchers who aren’t software engineers a way to run large-scale analyses to accelerate biology.
MIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years.
By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.