Retina Technology

This database could enhance the workflow of eye care professionals with its in-depth reference data for retinal layer thickness and optic nerve head metrics.

This device is designed to assist healthcare professionals in analyzing fundus images for the early detection of key retinal conditions.

The imaging system is designed to enable secure, real-time remote monitoring around the clock, from virtually any location.

This research project, titled, “A Generalizable Deep Learning Platform for Unifying Quantification of Experimental Autoimmune Uveitis.”

The UK-based company will debut the tool, called Dr.Noon CVD, at two conferences in March

The 15th annual meeting, taking from March 24–28 in Snowmass, Colorado, will deliver high-impact discussions on macular disease, artificial intelligence in ophthalmology, and breakthrough therapies—plus opportunities for networking on and off the slopes.

A recent study of AEYE-DS AI technology used in conjunction with the Topcon NW500 resulted in exceptional clinical diagnostic efficacy.

A look at the current state of AI in diabetic eye disease and where the future may take us.

The Sentinel Camera aims to address critical gaps in retinal disease screening by offering a portable device that captures high-quality images that require no dilation of the eye.

The NeurEYE research team will use millions of eye scans from Scottish optometrists to create the data set.

Cost among other factors may deter patients from screening, especially in rural and low-resource settings.

Within 4 months of AEYE-DS's deployment, diabetic retinopathy screening adherence increased from 29 percent to 49 percent.

In a study, a team of Korean researchers developed an AI model using OCT images to predict neovascular AMD treatment outcomes after anti-VEGF injections. The model highlights AI’s potential in personalized ophthalmic care.

Avant Technologies and Ainnova Tech have partnered to develop a low-cost retinal camera integrated with Ainnova’s Vision AI platform for early detection of ocular and systemic diseases. The technology will be marketed as a SaaS platform for primary care settings.

Options empower patients and providers to decrease treatment burden

A recent cohort study revealed low adoption of FDA-approved AI-based diabetic retinopathy detection, with less than 5% of diabetic patients receiving ophthalmic imaging. Researchers emphasize the need for improved awareness, cost-effectiveness, and integration to increase diabetic retinopathy screening rates.

Julie Schallhorn, MD, MS, also is an associate professor of ophthalmology at the University of California San Francisco, has drawn upon her bioengineering background to develop a device to simplify eye drop administration.

During a conversation at the American Academy of Ophthalmology annual meeting in Chicago, T.Y. Alvin Liu, MD, discussed plans for the James P. Gills Jr., MD, & Heather Gills Artificial Intelligence Innovation Center at the Wilmer Eye Institute at Johns Hopkins Medicine.

In a presentation at the American Academy of Ophthalmology annual meeting in Chicago, T.Y. Alvin Lu, MD, a retina specialist at Johns Hopkins Medicine, discussed the application of large language models (LLMs) in revenue cycle management (RCM).

In the first five months of the program at Henrietta Johnson Medical Center, 26% of patients with images gradable by EyeArt tested positive for either more-than-mild or vision-threatening diabetic retinopathy.

A home self-imaging device can provide ophthalmologists with actionable insight between office visits for AMD

AEYE Health will attend the American Academy of Ophthalmology (AAO) Annual Meeting, from October 18-21 in Chicago.

Applied Science, Inc. (ASI) is expanding its AdaptivMD chronic care workflow technology

A team of researchers at Arizona State University has developed tools to aid in the diagnosis of myopic maculopathy.