Protecting maternal health in Rwanda
An interdisciplinary team is developing a mobile health platform that uses AI to detect infection in Cesarean section wounds.
An interdisciplinary team is developing a mobile health platform that uses AI to detect infection in Cesarean section wounds.
Researchers develop a new method that uses multiple models to create more complex images with better understanding.
Researchers increase the accuracy and efficiency of a machine-learning method that safeguards user data.
Study finds computer models that predict molecular interactions need improvement before they can help identify drug mechanisms of action.
By modeling the conditions of an entire wind farm rather than individual turbines, engineers can squeeze more power out of existing installations.
The faculty members will work together to advance the cross-cutting initiative of the MIT Schwarzman College of Computing.
Algorithms designed to ensure multiple users share a network fairly can’t prevent some users from hogging all the bandwidth.
Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.
A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.
Piction Health, founded by Susan Conover SM ’15, uses machine learning to help physicians identify and manage skin disease.
Researchers develop tools to help data scientists make the features used in machine-learning models more understandable for end users.
This robotic system uses radio frequency signals, computer vision, and complex reasoning to efficiently find items hidden under a pile.
The second AI Policy Forum Symposium convened global stakeholders across sectors to discuss critical policy questions in artificial intelligence.
A new system lets robots manipulate soft, deformable material into various shapes from visual inputs, which could one day enable better home assistants.
MIT scientists unveil the first open-source simulation engine capable of constructing realistic environments for deployable training and testing of autonomous vehicles.