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.
By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.
Four early-career researchers shared their work on improving the social outcomes of artificial intelligence and machine learning at a research summit hosted by EECS Thriving Stars.
MIT alumni-founded Overjet analyzes and annotates dental X-rays to help dentists offer more comprehensive care.
Recent MEng graduates reflect on their application-focused research as affiliates of the MIT-IBM Watson AI Lab.