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

Report in 60 seconds. No Human Grading Needed.

EyeArt® AI Eye Screening System

The EyeArt system is the most extensively validated AI technology for autonomous detection of diabetic retinopathy, tested in the real-world on more than half million patients and nearly two million retinal images globally.

The EyeArt AI Eye Screening System 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.

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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Want to try EyeArt?

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

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


High Sensitivity & Specificity ⇒ Better Safety and Better Outcomes

Demonstrates over 91% referable DR screening sensitivity and specificity in a retrospective study of over 100,000 consecutive patient visits, with over 98.5% sensitivity in identifying patients with potentially treatable sight threatening DR.

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 100K Study     |    June 2017

Solanki et.al,Validation of EyeArt Automated Diabetic Retinopathy Screening System on Large Cohort of Mydriatic and Non Mydriatic Telescreening Data from EyePACS.” Investigative Ophthalmology & Visual Science 58, no. 8 (June 23, 2017): 3775–3775.

EyeArt Prospective, Multi-center Pivotal Clinical Trail     |    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

Unparalleled, Real World Clinical Validation

EyeArt is the most extensively validated AI technology in the world. 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 20,000 patients.

EyeArt 100K Study     |    June 2017

Solanki et.al,Validation of EyeArt Automated Diabetic Retinopathy Screening System on Large Cohort of Mydriatic and Non Mydriatic Telescreening Data from EyePACS.” Investigative Ophthalmology & Visual Science 58, no. 8 (June 23, 2017): 3775–3775.

UK NHS 20K Study     |    March 2017

Tufail et al.Automated Diabetic Retinopathy Image Assessment Software - Diagnostic Accuracy and Cost-Effectiveness Compared with Human Graders.” Ophthalmology 124, no. 3 (March 1, 2017):  343–351.

EyeArt vs 7-field ETDRS Study     |    October 2016

Solanki et.al.Clinical Validation Study of an Automated DR Screening System against 7-Field ETDRS Stereoscopic Reference Standard.” In AAO 2016. USA, 2016.

Solanki et.al.Comprehensive Clinical Validation Study of a Fully-Automated Diabetic Retinopathy Screening System Using Color Fundus Images against 7-Field ETDRS Stereoscopic Reference Standard.” In 16th EURETINA Congress. Copenhagen Denmark, 2016.

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 poor quality images or images not showing the required retinal fields (protocol deviations) automatically.

EyeArt provides grades as per the International Clinical DR (ICDR) severity scale. For many OUS markets EyeArt can be configured to provide grades as per UK NHS' s National Diabetic Eye Screening Programme (NDESP) 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 and with imaging protocols/cameras typically used in screening setups. 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).

Supports Multiple Camera Makes & Models

Out-of-the-box integration with fundus cameras from Canon, Topcon, and Nidek allows EyeArt to automatically pull retinal color fundus images soon after image capture and directly submit them to the cloud for DR screening. The EyeArt system has been designed to readily work with images from most table top color fundus cameras. Please contact us to find out if your camera is supported with EyeArt.

Easy-to-read reports in 60 seconds

The EyeArt system autonomously analyzes patient's retinal images to robustly detect lesions and 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 CE marking in the EU for sales as a Class IIa medical device and a Health Canada license for sales in Canada as a Class 2 device. In the US, the EyeArt System is limited to investigational use only. 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 been cleared for sales as a Class IIa medical device by EU and as a Class 2 medical device by Health Canada.

In the United States, EyeArt™ is limited by federal law to investigational use only and is not available for sale.

EyeMark™, EyeApp™, EyeSeeAMD™,  EyeSeeGlaucoma™ have not yet been cleared for sales in any region.

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