Immediate, Fully-automated, On-site Diabetic Retinopathy Screening

Report in 60 seconds. No Human Grading Needed.

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EyeArt® AI Eye Screening System

EyeArt is the first and only FDA cleared AI technology for autonomous detection of both more than mild and vision-threatening diabetic retinopathy, as well as the first and only AI system to be cleared by the FDA for use with multiple camera models from different manufacturers. It is the most extensively validated autonomous AI technology, tested in the real-world on more than half million patients and nearly two million retinal images globally.

EyeArt makes in-clinic, real-time diabetic retinopathy (DR) screening possible for primary care practices, diabetes centers and optometric offices by allowing physicians to quickly and accurately identify referable DR patients during a diabetic patient’s regular exam. EyeArt is indicated for use with Canon CR-2 AF, Canon CR-2 Plus AF, and Topcon NW400 cameras.

* EyeArt has US FDA clearance, CE marking as a class IIb medical device in the European Union, and a Health Canada license.

Vector camera

STEP 1

Capture color retinal fundus
images of the patient's eyes

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STEP 2

Submit images to the
cloud for analysis

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STEP 3

Download DR screening results and
export PDF report.

Easy to use. Detailed screening report.

Any physician can quickly and accurately detect referable diabetic retinopathy patients during a diabetic patient’s regular exam with a report that is generated in less than 60 seconds after submission of patient images.

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Indications for use
Labelling
Clinical studies
Regulatory

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EyeArt can be seamlessly integrated with your clinical workflow to enable automated DR screening. Click below to get started.

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* EyeArt has US FDA clearance, CE marking as a class IIb medical device in the European Union, and a Health Canada license.

Immediate, On-site Diabetic Retinopathy Screening

The EyeArt AI Eye Screening System makes in-clinic, real-time DR screening possible. Any physician can quickly and accurately detect referable diabetic retinopathy patients within minutes during a diabetic patient’s regular exam.

Once the patient fundus images have been captured and submitted to EyeArt, the DR screening results are available to view and export to a PDF report in less than a minute.

In the video below, diabetologist Prof. Dr. Med. Thomas Haak talks about how EyeArt AI Eye Screening System is helping screen for patients at risk of vision loss in their Diabetes Clinic in Bad Mergentheim, Germany

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High Sensitivity & Specificity ⇒ Better Safety and Better Outcomes

Demonstrated high sensitivity (96% for more than mild DR and 97% for vision-threatening DR) and high specificity (88% for more than mild DR and 90% for vision-threatening DR) in a pivotal, prospective, multicenter clinical trial.

High Sensitivity = Safety | High Specificity = Effectiveness

Can help ensure patients with silently progressing DR are identified in time for referral to an eyecare specialist while reducing unnecessary referrals. Can help focus on those patients with greatest need for care.

EyeArt Prospective, Multi-center Pivotal Clinical Trial     |    Nov 2021

Ipp et. al, “Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referable and Vision-threatening Diabetic Retinopathy,” JAMA Network Open, November 15, 2021.

    |    Apr 2019

Lim et.al, “Artificial Intelligence Screening for Diabetic Retinopathy: Analysis from a Pivotal Multi-Center Prospective Clinical Trial.” ARVO Imaging in the Eye Conference 2019. Vancouver, BC, Canada.

Jennifer I. Lim, MD, Marion H. Schenk Esq. Chair, Professor of Ophthalmology, and Director of Retina Service at the University of Illinois at Chicago presented the study data at the ARVO 2019 Imaging in the Eye Conference in Vancouver, Canada.

In part 1 of the interview, Lim shared about the growing need for diabetic retinopathy screening as the population of patients with diabetes continues to grow worldwide. Part 2 covered how the EyeArt system was trained and then tested in a clinical trial. In Part 3 (video below), Lim described the strong clinical trial results, stating that the EyeArt system achieved sensitivity of 95.5% and specificity of 86%.

Note: Dr. Lim has no conflicting financial disclosures

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Unparalleled, Real World Clinical Validation

EyeArt is the most extensively validated AI technology in the world. It has been validated in a pivotal, prospective, multicenter clinical trial against the rigorous clinical reference standard using the Early Treatment Diabetic Retinopathy Study (ETDRS) grading scale by experts at the University of Wisconsin Reading Center. It has been tested in a clinical validation study on over 100,000 patient visits, one of the largest data sets used to test any available DR screening technology, in demanding, real-world clinical environments using images captured in everyday practice. It has also been independently validated by UK NHS in a study with over 30,000 patients.

EyeArt Prospective, Multi-center Pivotal Clinical Trial     |    Nov 2021

Ipp et. al, “Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referable and Vision-threatening Diabetic Retinopathy,”, November 15, 2021. https://doi:10.1001/jamanetworkopen.2021.34254

EyeArt 100K Study*     |    August 2019

Bhaskaranand. et.al. “The Value of Automated Diabetic Retinopathy Screening with the EyeArt System: A Study of More Than 100,000 Consecutive Encounters from People with Diabetes.” Diabetes Technology & Therapeutics, July 23, 2019. https://doi.org/10.1089/dia.2019.0164.

UK NHS 30K Study*     |    Jun 2020

Heydon et al. “Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients,” British Journal of Ophthalmology 2021;105:723-728. https://bjo.bmj.com/content/105/5/723

*Evaluated on EyeArt versions that are different from the EyeArt version available for sale in the US

Truly automated, including image quality feedback

Fully automated DR screening, including imaging, grading for DR in accordance with internationally recognized standards and reporting, in a single office visit. No specialist needed for DR screening. EyeArt also flags cases with poor quality images or images not showing the required retinal fields (protocol deviations) automatically.

EyeArt provides grades based on the International Clinical DR (ICDR) severity scale.

When images of poor quality, or of insufficient retinal coverage are detected, EyeArt provides an ungradable output along with the reason in less than 1 minute, allowing the clinic to re-photograph the patient as needed.

Flexible, Robust, Secure, Cloud-based Design

The technology is designed to work effectively with image quality commonly encountered in diabetes patients. EyeArt is HIPAA compliant and keeps all data secure and private.

EyeArt system's RESTful API allows for seamless integration with 3rd party software and systems such as electronic health/medical records (EHR/EMR), picture archival and communication systems (PACS).

Easy-to-read reports in 60 seconds

The EyeArt system autonomously analyzes patient's retinal images to robustly detect signs of disease and returns an easy-to-read report in under 60 seconds. The report provides eye level and patient level diabetic retinopathy outputs and also indicates presence or absence of referable DR or vision threatening DR.

Click on the image to view sample EyeArt reports.

advisor-1

EyeArt could have a huge impact in improving the lives of individuals with diabetes who still face the risk of losing vision asymptomatically

Prof. Andrew Boulton, MD, DSc(Hon), FACP, FRCP

Renowned Diabetes Expert, Professor of Medicine, University of Manchester, UK
collaborators-2

I believe that an automated, reliable DR screening tool such as EyeArt would empower primary care providers to better manage their patients with diabetes.

Srinivas Sadda, MD

President and CSO, Doheny Eye Institute, Los Angeles, USA
collaborators-3

I believe that automation of common tasks like DR screening would have a tremendous impact on the quality and extent of vision care for the disparity populations. Therefore I am eager to work with EyeArt tool for DR screening.

Dr. Todd Margolis, MD, PhD

Distinguished Professor and Chairman, Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA (Former President of ARVO)
collaborators-1

...results of the large scale validation on over 100,000 patient encounters from the EyePACS database are highly encouraging and show that EyeArt can be a safe and effective alternative to manual screening.

Dr. Jorge Cuadros, OD, PhD

CEO of EyePACS, Assistant Clinical Professor, UC Berkeley School of Optometry, CA, USA
DrLaurenDaskivich

EyeArt’s automatic lesion detection and DR screening will allow us to better monitor our teleretinal patients at a lower cost in the under-resourced setting in which we care for Los Angeles’s most disadvantaged patients.

Dr. Lauren P. Daskivich, MD, MSHS

Director of Ophth. and Eye Health Programs, LA County Department of Health Services, Los Angeles, CA, USA

Technology behind EyeArt®

State of the Art Machine Learning

Our image analysis algorithms represent cutting-edge of research in image processing, computer vision, and machine learning. Technological innovations like multi-scale morphology-inspired filter banks are used with advanced deep learning algorithms to detect and localize lesions resulting from diabetic retinopathy.

Ultra-Secure Patient Data

EyeArt system's encrypted data storage and communication ensures that your data remains secure and private. EyeArt system has been independently audited to be HIPAA compliant.  Its RESTful API design enables seamless integration with existing electronic health record (EHR) systems and picture archival and communication systems (PACS) for secure operation.

Development and Partnerships

Development of the EyeArt system was partially supported by prestigious National Eye Institute (NEI/NIH) grants (EB013585, EY026864, EY027241) totaling over $4.1M USD. In addition, the NIH also partially funded Eyenuk’s U.S. clinical trials for EyeArt.

Eyenuk has collaborated with the Doheny Eye Institute, Los Angeles and with EyePACS from the earliest stages for the development of the cloud-based EyeArt system.

Registration and Regulatory Information

The EyeArt AI Eye Screening System was developed with funding from the US National Institutes of Health (NIH) and is validated by the UK National Health Service (NHS). The EyeArt System has US FDA clearance, CE marking in the EU for sales as a Class IIb medical device and a Health Canada license for sales in Canada as a Class 2 device. For use in other countries, please contact us.

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* Products were supported by Award numbers R44EB013585, R42TR000377, R44TR000377, R43EY024848, R43EY025984, SB1EY027241, and R43EY028081 from the National Institutes of Health (NIH). The content is solely the responsibility of Eyenuk, Inc. and does not necessarily represent the official views of NIH.

** The devices are covered by one or more of the following US patents and their foreign counterparts: 8879813, 8885901, 9002085, and 9008391. Additional patents are pending.

EyeArt has US FDA clearance and Health Canada license for the autonomous detection of DR. It has CE marking as a class IIb medical device in the European Union, under EU MDR for the autonomous detection of DR, AMD, and glaucomatous optic nerve damage.

EyeMark™, EyeReadUWF™ have not yet been cleared for sales in any region.

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