Diabetic retinopathy, an eye disorder caused by diabetes, is the primary cause of blindness in America and over 99% of cases in India. India and China currently account for over 90 million diabetic patients and are on the verge of an explosion of diabetic populations. This may result in an unprecedented number of persons becoming blind unless diabetic retinopathy can be detected early. Aravind Eye Hospitals is the largest eye care facility in the world, handling over 2 million patients per year. The hospital is on a massive drive throughout southern India to detect diabetic retinopathy at an early stage. To that end, a group of 10-15 physicians are responsible for manually diagnosing over 2 million retinal images per year to detect diabetic retinopathy. While the task is extremely laborious, a large fraction of cases turn out to be normal indicating that much of this time is spent diagnosing completely normal cases. This paper describes our early experiences working with Aravind Eye Hospitals to develop an automated system to detect diabetic retinopathy from retinal images. The automated diabetic retinopathy problem is a hard computer vision problem whose goal is to detect features of retinopathy, such as hemorrhages and exudates, in retinal color fundus images. We describe our initial efforts towards building such a system using a range of computer vision techniques and discuss the potential impact on early detection of diabetic retinopathy.
LOS ANGELES--(BUSINESS WIRE)--Eyenuk Inc., a global artificial intelligence (AI) medical technology and services company and the leader in real-world applications for AI Eye Screening, announced today that the EyeArt AI Eye Screening System was deployed successfully for Italy's first national prevention and diagnosis campaign for retinal and diabetic maculopathy. A total of 2,200 patients were screened at 30 centers across Italy, with more than half chosen for EyeArt AI Eye Screening. The Month of Prevention of Diabetic Retinopathy and Maculopathy was sponsored by the Italian Ministry of Health, the city of Milan and the Italian Ophthalmology Society in collaboration with the Ambrosian Ophthalmic Center (CAMO), San Raffaele Hospital and Eyenuk. In Italy, an estimated 3.2 million patients have diabetes. As many as 25% are estimated to be affected by diabetic retinopathy (DR),1 the main cause of vision impairment and blindness among working-age adults.
In an evaluation of retinal photographs from adults with diabetes, an algorithm based on deep machine learning had high sensitivity and specificity for detecting referable diabetic retinopathy, according to a study published online by JAMA. Among individuals with diabetes, the prevalence of diabetic retinopathy is approximately 29 percent in the United States. Most guidelines recommend annual screening for those with no retinopathy or mild diabetic retinopathy and repeat examination in 6 months for moderate diabetic retinopathy. Retinal photography with manual interpretation is a widely accepted screening tool for diabetic retinopathy. Automated grading of diabetic retinopathy has potential benefits such as increasing efficiency and coverage of screening programs; reducing barriers to access; and improving patient outcomes by providing early detection and treatment.
The FDA has permitted marketing of IDx-DR (IDx LLC)--the first medical device to use artificial intelligence to detect greater than a mild level of the eye disease diabetic retinopathy in adults who have diabetes. Diabetic retinopathy occurs when high levels of blood sugar lead to damage in the blood vessels of the retina, the light-sensitive tissue in the back of the eye. Diabetic retinopathy is the most common cause of vision loss among the more than 30 million Americans living with diabetes and the leading cause of vision impairment and blindness among working-age adults. "Early detection of retinopathy is an important part of managing care for the millions of people with diabetes, yet many patients with diabetes are not adequately screened for diabetic retinopathy since about 50% of them do not see their eye doctor on a yearly basis," said Malvina Eydelman, MD, Director of the Division of Ophthalmic, and Ear, Nose, and Throat Devices at the FDA's Center for Devices and Radiological Health. "Today's decision permits the marketing of a novel artificial intelligence technology that can be used in a primary care doctor's office.
Eyenuk, Inc., a global artificial intelligence (AI) medical technology and services company and the leader in real-world applications for AI Eye Screening, announced that it has successfully fulfilled the contract awarded by Public Health England (PHE) to use Eyenuk's EyeArt AI Eye Screening System to grade 60,000 patient image sets from 6 different National Health Service (NHS) Diabetic Eye Screening Programmes in England. Diabetic retinopathy (DR) is a vision-threatening complication of diabetes and a leading cause of preventable vision loss globally.1 In England, an estimated 4.6 million are living with diabetes, one-third of whom are at risk of developing DR. Diabetes has become a growing health concern as the number of people diagnosed with diabetes in the U.K. has more than doubled in the last 20 years.2 The U.K. has been leading the world in diabetic retinopathy screening, achieving patient uptake rates of over 80% (screening nearly 2.5 million diabetes patients annually),3 as compared with most parts of the world where typically less than half of diabetes patients receive annual eye screening.4