NEI Research News

Researchers at the National Institutes of Health applied artificial intelligence (AI) to a technique that produces high-resolution images of cells in the eye. They report that with AI, imaging is 100 times faster and improves image contrast 3.5-fold.

Research shows that an artificial intelligence technology developed with NEI funding can accurately and independently detect all severe cases of retinopathy of prematurity.

A study of children and youth with diabetes concludes that diabetic eye exams using artificial intelligence (AI) increase completion rates of screenings to detect diabetic eye disease.

Using a technique they developed for studying eye fluid, Stanford Medicine researchers and their collaborators have found a way to measure ocular aging, opening avenues for treatment of numerous eye diseases.

Researchers have used artificial intelligence models and machine-learning algorithms to successfully predict which components of amino acids that make up therapeutic proteins are most likely to safely deliver therapeutic drugs to animal eye cells.

An inexpensive, smartphone-based camera can help doctors identify premature infants needing treatment for retinopathy of prematurity (ROP), according to a new study funded by the National Eye Institute (NEI).

Scientists have decoded visual images from a dog’s brain, offering a first look at how the canine mind reconstructs what it sees.

Researchers at Brown University developed a new model to predict human flocking behavior based on optics and other sensory data.

Scientists have developed an artificial intelligence system that can analyze eye scans taken during a routine visit to an optician or eye clinic and identify patients at a high risk of a heart attack.

National Eye Institute researchers developed and validated an artificial-intelligence-based method to evaluate patients with Stargardt, an eye disease that can lead to childhood vision loss.