A new way to calculate global intensive care unit mortality risk
The GOSSIS algorithm was developed using data from hospitals around the world to spur greater multi-center collaboration and improved benchmarking.
Big issues on the table at the MIT Sloan Sports Analytics Conference
MIT’s sports-analytics showcase features open talk on some large topics in pro and amateur athletics, from player satisfaction to data equity.
Q&A: Meet the former all-star pitcher turned MIT student
Chris Capuano, an analytics-friendly Major-Leaguer, pursues his MBA in the Sloan Fellows Program.
Supercomputers can spot cyber threats
Lincoln Laboratory researchers have developed a technique to compress hours of internet traffic into a bundle that can be analyzed for suspicious behavior.
Twenty-five ways in which MIT has transformed computing
From digital circuits to ingestible robots, the Institute has helped spearhead key innovations in the technology revolution.
Achieving greater efficiency for fast data center operations
System better allocates time-sensitive data processing across cores to maintain quick user-response times.
Exploring the nature of intelligence
Undergraduate research projects show how students are advancing research in human and artificial intelligence, and applying intelligence tools to other disciplines.
Putting data privacy in the hands of users
New platform forces data center servers to only use data in ways that users explicitly approve.
Predicting sequence from structure
Researchers have devised a faster, more efficient way to design custom peptides and perturb protein-protein interactions.
Learning to teach to speed up learning
An algorithm that teaches robot agents how to exchange advice to complete a task helps them learn faster.
Filling the gaps in a patient’s medical data
Neural network assimilates multiple types of health data to help doctors make decisions with incomplete information.
Julia Lab joins team to speed up drug approval process
Health Analytics Collective uses real-world evidence to modernize health and drug development decisions.
Identifying artificial intelligence “blind spots”
Model identifies instances when autonomous systems have learned from examples that may cause dangerous errors in the real world.
AI, the law, and our future
MIT “Policy Congress” examines the complex terrain of artificial intelligence regulation.
Democratizing artificial intelligence in health care
Hackathons promote doctor-data scientist collaboration and expanded access to electronic medical-records to improve patient care.