In the United States, there are more than 30 million people with diabetes and up to 30% of them may have diabetic retinopathy (DR), the leading cause of working-age adult blindness. Since patients with diabetes outnumber eye-care professionals by 700 to 1, there aren’t enough eye-care professionals to provide screening for this growing population.

The use of artificial intelligence (AI) is rapidly emerging as a meaningful tool for autonomous DR detection when eye care expertise is unavailable and for augmenting the skills of optometrists to provide secondary grading of DR and ensure appropriate referrals for patients who are most likely to benefit from it. In a recent article titled, “Embrace, not fear, AI in diabetic retinopathy,” Dr. Paul Chous made the case for AI-assisted workflow to optometrists: “[AI] may help eye care practitioners improve their staging and referral acumen and ensure delivery of therapy to patients who are most likely to benefit from it. AI is not a cure-all for DR detection and staging, but it might help to preserve vision at a population level and improve care. AI advancements are unlikely to take anyone’s job, but they will likely make for better doctors.”

In this webinar, Dr. Michael Ip from the Doheny Eye Institute at UCLA summarized the FDA pivotal clinical trial results for autonomous DR detection by the EyeArt system, and with real clinical case examples, Dr. Paul Chous illustrated how Eyenuk’s EyeScreen™ Human+AI platform supports optometrists’ DR screening workflow, which combines human grading and AI assessment to optimize detection and grading of DR.

View recorded webinar below.