Deep-learning model takes a personalized approach to assessing each patient’s risk of lung cancer based on CT scans.

Researchers experimentally evaluated the impact biased AI recommendations have on emergency decisions, where participants responded to mental health crises by calling for either medical or police assistance.

New technique significantly reduces training and inference time on extensive datasets to keep pace with fast-moving data in finance, social networks, and fraud detection in cryptocurrency.

MIT CSAIL researchers solve a differential equation behind the interaction of two neurons through synapses to unlock a new type of speedy and efficient AI algorithm.

Researchers make headway in solving a longstanding problem of balancing curious “exploration” versus “exploitation” of known pathways in reinforcement learning.

MIT researchers have developed a machine-learning technique that accurately captures and models the underlying acoustics of a scene from only a limited number of sound recordings. In this image, a sound emitter is marked by a red dot. The colors show the sound volume if a listener were to stand at different locations — yellow is louder and blue is quieter.

Researchers increase the accuracy and efficiency of a machine-learning method that safeguards user data.