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

A combination of routine eye scans and AI has created a powerful new way for measuring short-sightedness to better predict people's long-term risk of serious retinal damage, a new study suggests.

A statistical active appearance model (AAM) is developed to track and detect eye blinking. The model has been designed to be robust to variations of head pose or gaze. In particular we analyze and ...

Survival models using electronic health record data show promise in predicting progression to proliferative diabetic ...

Model Explorer offers an intuitive and hierarchical visualization of model graphs. It organizes model operations into nested layers, enabling users to dynamically expand or collapse these layers. It ...

Discover how BlockDAG’s Seattle sports partnerships, Ethereum’s $5K goal, and Celestia’s rollup gains make them the popular ...

A novel AI-powered retina tracker can analyze retinal images with near-perfect accuracy in under one second, according to a study being presented Monday at ENDO 2025, the Endocrine Society’s annual ...

We're almost at the final level of Amazon's four-day Prime Day 2025, but you can still power up your PC gaming with big ...

Recent advances in brain imaging techniques require the development of advanced models of brain networks and graphs. Previous work on percolation on lattices and random graphs demonstrated emergent ...

Research in animal models has shown that numerous properties of optical defocus, such as sign, degree and retinal distribution, have substantial effects on eye growth. The sign of the imposed optical ...