Researchers from UW Medicine have found that artificial intelligence-based screening algorithms to diagnose diabetic retinopathy do not perform as well as they claim.

The IQA is a software system intended for use in importing, displaying, analyzing and managing images acquired with digital fundus cameras. The patented software detects the most common causes of retinal imaging artifacts.

New York University researchers created a “developmental atlas” of gene expression in neurons, using gene sequencing and machine learning to categorize more than 250,000 neurons in the brains of fruit flies.

A new paper in Current Biology details how neurons in area V4, the first stage specific to the brain’s object vision pathway, represent 3D shape fragments, not just the 2D shapes used to study V4 for the last 40 years.

Researchers have developed a neural network capable of recognizing retinal tissues during the process of their differentiation in a dish.

Caltech researchers have combined tools from machine learning and neuroscience to discover that the brain uses a mathematical system to organize visual objects according to their principal components. The work was published June 3 in Nature.

Computer model of face processing could reveal how the brain produces richly detailed visual representations so quickly.

An artificial intelligence algorithm that can detect a potentially devastating cause of childhood blindness better than most human experts has been granted breakthrough status by the FDA.

Study from Columbia University uncovers human-like brain circuit at work. Their findings lay the groundwork for mapping mechanisms of color vision.

Researchers at Baylor College of Medicine and the University of Tübingen in Germany have developed a novel computational approach to finding stimuli that neurons in the brain ‘like.’