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The EyeArt system is cleared for use in adults who have been diagnosed with diabetes but have not been previously diagnosed with retinopathy. It is intended for use in frontline healthcare settings by trained professionals.
The EyeArt system is cleared for the autonomous detection of diabetic retinopathy, age-related macular degeneration, and glaucomatous optic nerve damage in adults with diabetes. This gives clinicians the actionable data to prioritize referrals for high-risk patients.
We recognize that every health system has a unique technical ecosystem. Eyenuk provides comprehensive collaboration to integrate EyeArt results into your specific EHR environment using industry-standard protocols. Our team partners with your IT and clinical leadership to navigate the nuances of your workflow, ensuring results are properly documented in the patient’s permanent record and manual data entry is minimized.
EyeArt is compatible for use with multiple retinal camera models from different manufacturers globally. This flexibility allows health systems to leverage existing hardware or choose the best fit for their clinics.
No. EyeArt is an autonomous AI, meaning it provides a definitive diagnostic result at the point of care without requiring an overread by an ophthalmologist. This allows primary care teams to relay the AI-generated findings and facilitate necessary specialist referrals during the patient’s routine diabetes checkup.
The analysis is nearly instantaneous. Once the retinal images are captured and uploaded, the AI provides a result in under 30 seconds, enabling immediate clinical decision-making while the patient is still in the office.
The platform includes real-time image quality feedback. If a captured image does not meet the necessary quality threshold for a definitive analysis, the system immediately notifies the operator so they can retake the photo while the patient is still positioned at the camera.
No. EyeArt is cleared as a non-mydriatic solution. Most patients can be screened effectively without the need for dilating drops, which improves patient comfort, reduces visit time, and simplifies the workflow for the primary care team.
Eyenuk maintains enterprise-grade security protocols, including GDPR compliance and SOC 2 Type 2 attestation. All patient data is protected with high-level encryption both at rest and during transit to ensure the highest standards of data privacy.
Eyenuk provides a structured onboarding program for medical assistants and nursing staff. Since the AI provides real-time feedback on image quality, staff can be trained quickly to capture high-quality, gradable images, making the system easy to adopt in high-volume primary care settings.
Eyenuk was founded in 2010 by Dr. Kaushal Solanki, who led a multidisciplinary team of experts in artificial intelligence, medical imaging, and clinical research. Together, they developed the foundational deep-learning algorithms that became EyeArt, fueled by a shared mission to eliminate preventable blindness. The team’s unique combination of technological innovation and rigorous clinical validation was essential in creating a solution that addresses the global shortage of expert eye care for millions living with diabetes.