We are pleased to announce the release of the beta version of our automated AI system for early detection of Diabetic Retinopathy. Our solution

We are currently partnering with a national tele-ophthalmology group and conducting a field trial in over 150 screening centers for our automated solution for early detection of Diabetic Retinopathy.

An overview of the solution and its major components is as follows:

Patient’s retinal images are captured via Fundus Cameras at local screening centers or clinics, and are uploaded via the web to a cloud-based server for further processing.

A cloud-based web application for patient registration and data entry, image capture and uploading, integration with the AI model, remote diagnosis by trained specialists, as well as patient reporting, messaging and notification.

Automated AI Diagnosis: The AI model runs on a remote server and automatically diagnose and classify the image nearly instantly as either normal or showing evidence of DR, the stage of the DR, along with the probability of the model’s predicted diagnosis.

 Remote Human Diagnosis: Eye-care professionals can login remotely to the web application to
review and validate the AI diagnosis, add notes, provide referral to a specialist, follow-up and treatment options. The system design also incorporates the ability to fine-tune the AI algorithm based on corrections of diagnosis errors by the specialists.

Integrated administrative, reporting, and messaging for patient communication, system performance reports, and overall statistics.