Using machine learning to estimate risk of cardiovascular death
CSAIL system uses a patient's ECG signal to estimate potential for cardiovascular death.
CSAIL system uses a patient's ECG signal to estimate potential for cardiovascular death.
MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.
“Risk-aware” traffic engineering could help service providers such as Microsoft, Amazon, and Google better utilize network infrastructure.
Tracy Slatyer hunts through astrophysical data for clues to the invisible universe.
Report catalogs, analyzes available open-source publishing software; warns open publishing must grapple with siloed development and community-owned ecosystems.
Technique can spot anomalous particle smashups that may point to phenomena beyond the Standard Model.
Study finds online restaurant information can closely predict key neighborhood indicators, in lieu of other data.
Open access journal to promote the latest research, educational resources, and commentary from leading minds in data science.
At MIT, Luis Videgaray, alumnus and former foreign minister of Mexico, will launch project to help shape international AI policies.
L4DC explored an emerging scientific area at the intersection of real-time physical data, machine learning, control theory, and optimization.
System lets nonspecialists use machine-learning models to make predictions for medical research, sales, and more.
General-purpose language works for computer vision, robotics, statistics, and more.
MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.
Program creates a new hub for pedagogy and research in time-based media.
Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.