Making genetic prediction models more inclusive
MIT computer scientists developed a way to calculate polygenic scores that makes them more accurate for people across diverse ancestries.
Download RSS feed: News Articles / In the Media / Audio
MIT computer scientists developed a way to calculate polygenic scores that makes them more accurate for people across diverse ancestries.
James Fujimoto, Eric Swanson, and David Huang are recognized for their technique to rapidly detect diseases of the eye; Subra Suresh is honored for his commitment to research and collaboration across borders.
StructCode, developed by MIT CSAIL researchers, encodes machine-readable data in laser-cut objects by modifying their fabrication features.
Center for Ultracold Atoms gets funding boost to “punch through tough scientific barriers and see what's on the other side.”
Researchers coaxed a family of generative AI models to work together to solve multistep robot manipulation problems.
Some researchers see formal specifications as a way for autonomous systems to "explain themselves" to humans. But a new study finds that we aren't understanding.
Five MIT faculty, along with seven additional affiliates, are honored for outstanding contributions to medical research.
MIT engineers develop a long, curved touch sensor that could enable a robot to grasp and manipulate objects in multiple ways.
MIT Digital Learning Lab advances quality digital learning on campus and globally.
Open-source software by MIT MAD Fellow Jonathan Zong and others in the MIT Visualization Group reveals online graphics’ embedded data in the user’s preferred degree of granularity.
By focusing on causal relationships in genome regulation, a new AI method could help scientists identify new immunotherapy techniques or regenerative therapies.
Grants fund studies of honeybee tracking, glass building materials, and defining excellence in human movement.
With the growing use of AI in many disciplines, the popularity of MIT’s four “blended” majors has intensified.
Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.
Co-directors Youssef Marzouk and Nicolas Hadjiconstantinou describe how the standalone degree aims to train students in cross-cutting aspects of computational science and engineering.