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
Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.
Researchers find nonclinical information in patient messages — like typos, extra white space, and colorful language — reduces the accuracy of an AI model.
Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.
New type of “state-space model” leverages principles of harmonic oscillators.
MAD Fellow Alexander Htet Kyaw connects humans, machines, and the physical world using AI and augmented reality.