AEYE Health provides FDA-cleared AI algorithms for the instant diagnosis of diabetic retinopathy using a single retinal image captured by handheld or desktop cameras. This technology enables point-of-care screening, addressing the significant gap in diabetic eye care by facilitating timely detection and treatment for millions at risk of vision loss.
Funding
$28.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Millions of people with diabetes are at risk of developing diabetic retinopathy, a condition that can lead to blindness if left undiagnosed and untreated. Traditional screening methods require specialist referrals, leading to low adherence rates due to a shortage of ophthalmologists, high costs, and lack of accessibility. This results in delayed detection and intervention, increasing the risk of vision loss.
Solution
AEYE Health provides an AI-based diagnostic screening system that enables instant diagnosis of diabetic retinopathy using a single retinal image captured by handheld or desktop cameras. The technology facilitates point-of-care screening in primary care settings, retail pharmacies, and other healthcare facilities, eliminating the need for specialist referrals in most cases. The AI model analyzes retinal images to detect signs of diabetic retinopathy, even in early stages where complications may not be visible to the human eye. This allows for timely intervention and treatment, preventing potential vision loss and improving patient outcomes.
Target Audience
The primary target audience includes primary care physicians, endocrinologists, and other healthcare providers who manage patients with diabetes, as well as retail pharmacies and screening facilities seeking to offer accessible and convenient diabetic retinopathy screening.
Features
- FDA-cleared AI algorithms for instant diagnosis of diabetic retinopathy
- Single-image-per-eye solution, reducing screening time to approximately one minute
- Compatible with both desktop and handheld retinal cameras
- High sensitivity (93%) and specificity (91.4%) in clinical trials
- Non-mydriatic imaging, rarely requiring dilation
- AI model capable of detecting early-stage diabetes signs in seemingly healthy retinas
- CPT code 92229 for AI diabetic retinopathy screening reimbursement