Medical imaging and radiology
Aidoc
Clinical AI platform for radiology and enterprise imaging workflows.
Last updated: June 5, 2026
Back to directoryEyenuk EyeArt medical AI product profile
FDA-cleared autonomous diabetic retinopathy screening system that analyzes retinal images and returns patient-level and eye-level screening results.
Medical imaging and radiology
Best fit
Diabetes and primary-care workflows that need in-clinic diabetic eye screening with supported cameras, trained operators, referral rules, and clinician oversight.
- Primary use case
- Autonomous AI diabetic retinopathy screening from color retinal fundus images
- Audience
- Primary care clinics, diabetes programs, optometry groups, ophthalmology referral networks, and health systems
- Risk level
- High
- Pricing signal
- Provider deployment pricing; request current camera, integration, reimbursement, and service terms.
- Official sources
- 5 official sources
Compare within workflow: Medical imaging and radiology · comparison shortlist · source index
Regulatory, privacy, evidence, and workflow lens
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. |
Where Eyenuk EyeArt fits
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.
What to verify before using Eyenuk EyeArt
- FDA 510(k) record, current EyeArt version, supported camera models, intended-use language, and eligible patient population.
- Required operator training, image-quality feedback, unreadable-image handling, referral instructions, and patient-report delivery.
- How retinal images, PHI, reports, API integrations, storage, encryption, audit logs, and EHR/PACS connections are governed.
- Local performance for image quality, unreadable exams, false positives, false negatives, follow-up completion, equity, and eye-care referral capacity.
Source links
Use these links to confirm current claims, terms, regulatory status, pricing, and deployment requirements.
- www.eyenuk.com / us-en / products
- www.eyenuk.com / us-en / articles
- www.accessdata.fda.gov / scripts / cdrh
- www.accessdata.fda.gov / scripts / cdrh
- www.eyenuk.com / en / privacy-policy
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