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.
System could help with diagnosing and treating noncommunicative patients.
UROP student Sonia Reilly studies the math of machine learning to improve predictions of natural disasters.
Computer Science and Artificial Intelligence Laboratory team creates new reprogrammable ink that lets objects change colors using light.
New capabilities allow “roboats” to change configurations to form pop-up bridges, stages, and other structures.
New approach harnesses the same fabrication processes used for silicon chips, offers key advance toward next-generation computers.
Nearly $12 million machine will let MIT researchers run more ambitious AI models.
MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.
Submerged system uses the vibration of “piezoelectric” materials to generate power and send and receive data.
Prototype machine-learning technology co-developed by MIT scientists speeds processing by up to 175 times over traditional methods.
“Risk-aware” traffic engineering could help service providers such as Microsoft, Amazon, and Google better utilize network infrastructure.
In “semiautonomous” cars, older drivers may need more time to take the wheel when responding to the unexpected.
New research from the Computer Science and Artificial Intelligence Laboratory uses machine learning to customize clothing designs.