MIT scientists investigate memorization risk in the age of clinical AI
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
Public health
Simpler models can outperform deep learning at climate prediction
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
Accelerating scientific discovery with AI
FutureHouse, co-founded by Sam Rodriques PhD ’19, has developed AI agents to automate key steps on the path toward scientific progress.
AI in health should be regulated, but don’t forget about the algorithms, researchers say
In a recent commentary, a team from MIT, Equality AI, and Boston University highlights the gaps in regulation for AI models and non-AI algorithms in health care.
Equipping doctors with AI co-pilots
Alumni-founded Ambience Healthcare automates routine tasks for clinicians before, during, and after patient visits.
How an archeological approach can help leverage biased data in AI to improve medicine
Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.
Supporting sustainability, digital health, and the future of work
The MIT and Accenture Convergence Initiative for Industry and Technology selects three new research projects to support.
Gamifying medical data labeling to advance AI
MIT alumnus’ platform taps the wisdom of crowds to label medical data for AI companies.