AEYE-DS
FDA-cleared autonomous AI diagnostic screening system for more-than-mild diabetic retinopathy in eligible adults with diabetes.
Last updated: June 14, 2026
Back to directoryFDA-cleared autonomous diabetic retinopathy screening system that analyzes retinal images and returns patient-level and eye-level screening results.
Diabetes and primary-care workflows that need in-clinic diabetic eye screening with supported cameras, trained operators, referral rules, and clinician oversight.
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| Status | FDA 510(k)-cleared diabetic retinopathy detection device for EyeArt v2.2.0. |
|---|---|
| Review route | 510(k) K223357, with EyeArt K200667 as the predicate device trail. |
| Intended use | Automatically detects more than mild diabetic retinopathy and vision-threatening diabetic retinopathy in eyes of adults diagnosed with diabetes who have not previously been diagnosed with diabetic retinopathy, using Canon CR-2 AF, Canon CR-2 Plus AF, or Topcon NW400 cameras. |
| Verification note | Confirm the deployed EyeArt version, supported camera, image-quality workflow, adult diabetes eligibility, prior-retinopathy exclusion, operator training, and referral instructions before using autonomous screening results. |
| Source | www.accessdata.fda.gov / cdrh_docs / pdf22 |
Product-specific review. These product-specific signals summarize what the cited sources imply before treating Eyenuk EyeArt as safe for a local clinical, operational, or research workflow.
| Regulatory / FDA | Match deployment to the current FDA-cleared EyeArt version, indication, supported cameras, trained-user requirements, adult diabetes population, geography, and referral workflow. |
|---|---|
| Privacy | Review retinal-image upload, cloud processing, API integrations, EHR/PACS connectivity, encryption, retention, support access, audit logging, BAA terms, and privacy/security contacts before sending PHI. |
| Evidence | Validate performance locally across camera model, operator skill, image quality, disease prevalence, patient demographics, false-positive burden, missed-referral risk, and follow-up completion. |
| Workflow | Best governed as an autonomous screening workflow with eligibility checks, trained image capture, report review, referral routing, documentation, billing, and post-deployment quality monitoring. |
Eyenuk describes EyeArt as an FDA-cleared autonomous AI eye-screening system for more-than-mild and vision-threatening diabetic retinopathy; FDA records list EyeArt K200667 and EyeArt v2.2.0 K223357 as diabetic-retinopathy detection devices, while Eyenuk materials describe supported cameras, cloud workflow, security, and privacy contacts.
Not for: Comprehensive eye exams, use outside the cleared adult diabetes population, unsupported camera models, or diagnosis without the required imaging and referral workflow.
Use these links to confirm current claims, terms, regulatory status, pricing, and deployment requirements.