Matthew Leming, Ph.D., and Hyungsoon Im, Ph.D. of the Center for Systems Biology at Massachusetts General Hospital, are the ...

Explore the evolution of image annotation—from manual labeling to AI automation—powering innovations in healthcare, retail, ...

In the race to develop AI that understands complex images like financial forecasts, medical diagrams and nutrition labels—essential for AI to operate independently in everyday settings—closed-source ...

Researchers from Okinawa Institute of Science and Technology outline a strategy for using machine learning (ML) to address ...

AI is revolutionizing flood victim searches by rapidly scanning drone imagery to pinpoint debris that may hide bodies, enabling responders to focus their efforts where it counts.

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to ...

Library for efficient training and application of Machine Learning Interatomic Potentials (MLIP) - instadeepai/mlip ...

AI offers promise in the realm of chronic disease management, including diabetes, obesity, and PCOS, but must be approached with caution.

In the case of flooding, human remains may be tangled among vegetation and debris. Therefore, a system could identify clumps ...

Recent successes in applying computer vision and machine learning to drone imagery for rapidly determining building and road damage after hurricanes or shifting wildfire lines suggest that AI could be ...

Deep learning using fundus and optical coherence tomography imaging may identify mental disorders during routine eye exams.

AI models are trained to optimize outputs, but in educating children, the process is the point. If we assess children only in ...