By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases
BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.
Helping scientists run complex data analyses without writing code
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.
AI maps how a new antibiotic targets gut bacteria
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.
New AI system could accelerate clinical research
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.
3Qs: Caroline Uhler on biology and medicine’s “data revolution”
Caroline Uhler is Andrew (1956) and Erna Viterbi Professor of Engineering; Professor of EECS and in IDSS; and Director of the Eric and Wendy Schmidt Center at the Broad Institute of MIT and Harvard, where she is also a core institute and scientific leadership team member. Next year, she’ll deliver a sectional lecture to the International Congress of Mathematicians at their annual congress in Philadelphia, a high honor.
Building a lifeline for family caregivers across the US
Ianacare, co-founded by Steven Lee ’97, MEng ’98, equips caregivers with the resources, networks, and tools they need to support loved ones.
Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event
Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.