RETINA-AI Health develops the Galaxy system, an automated diabetic retinopathy screening tool that utilizes deep learning to analyze retinal images and provide diagnoses in under 10 seconds without the need for on-site eye care specialists. This technology addresses the high risk of blindness from diabetic retinopathy by enabling early detection and timely referrals in primary care settings.
Funding
$12.3M 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
Diabetic retinopathy, a leading cause of blindness in working-age adults, often goes undetected until it's advanced, due to the need for specialized equipment and trained professionals for screening. This results in delayed diagnoses and treatment, increasing the risk of vision loss.
Solution
RETINA-AI Health's Galaxy system offers an automated solution for diabetic retinopathy screening, delivering diagnoses in under 10 seconds. The system uses deep learning to analyze retinal images, eliminating the need for on-site eye care specialists and enabling early detection in primary care settings. The AI identifies markers indicative of moderate or worse diabetic retinopathy (mowDRet), prompting referrals to eye care professionals when necessary, while patients without detected disease are scheduled for a retest in 12 months. The system is compatible with multiple robotic cameras, simplifying image capture and analysis.
Target Audience
The primary target audience includes primary care physicians (PCPs), insurers/payors, and patients seeking convenient and early detection of diabetic retinopathy.
Features
- AI-powered analysis of retinal images for diabetic retinopathy detection
- Diagnosis provided in under 10 seconds
- Compatibility with robotic cameras from Centervue, Crystalvue, and Topcon
- High sensitivity (exceeding 90% for mowDRet and 95% for vision-threatening diabetic retinopathy)
- Actionable report aligned with American Academy of Ophthalmology (AAO) guidelines
- Easy-to-use interface requiring minimal training for medical assistants
- Integration with existing primary care workflows
- Reimbursement via CPT code 92229