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Artificial intelligence used to combat blindness


The focus of the research is with the application of deep-learning methods to produce an automated algorithm designed to detect diabetic retinopathy from the scanning of images of the eye. The technology is a type of'deep learning'. Deep Learning is a new area of machine learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: 'true' Artificial Intelligence. The algorithm is based on more than 75,000 images, taken from the back of the eye, and relating to a wide range of patients representing several ethnicities. The images included a mix of health patients and those with the condition.

New AI system detects retinopathy with 95.5% accuracy


A new artificial intelligence system is capable of detecting diabetic retinopathy 95.5% of the time. The technology was described at the annual meeting of the American Academy of Ophthalmology (12โ€“15 October, San Francisco). The system, named EyeArt, was used to screen 893 patients with diabetes in 15 different medical locations. It can provide a reading within 60 seconds. EyeArt displayed 95.5% sensitivity and 86% specificity, while more than 90% of eyes flagged as positive by the system had diabetic retinopathy or another eye disease.

Google successfully uses machine learning to detect diabetic retinopathy


Diabetes is a hell of a disease. While many people view it as nothing more than the inability to eat sweets, it is actually much more devastating than just that. If untreated, having high glucose levels can wreak havoc on a patient's body -- these folks can go blind, have limbs amputated, or worst of all, die. Diabetic eye disease is caused by retinopathy. Affected diabetics can have small tears inside the eye, causing bleeding.

AI system allows accurate retinopathy diagnosis by non-ophthalmologists


Accurate, automated retinal screening is an important development for the millions of diabetic patients who require annual examination for sight-threatening diabetic retinopathy. New research, presented at the 123rd Annual Meeting of the American Academy of Ophthalmology (12โ€“15 October 2019, CA, USA) โ€“ demonstrates that an automated, artificial intelligence (AI) screening system can detect diabetic retinopathy with more than 95% accuracy. Approximately 25% of diabetic individuals in the USA will develop retinopathy. Initially, such retinal damage may be asymptomatic, but can ultimately lead to blindness. There are various options available for the treatment of diabetic retinopathy, however, early diagnosis significantly improves treatment effectiveness.

First-of-its-Kind AI Tool for Diabetic Retinopathy Detection Approved by FDA


The AI-powered, cloud-based system will be available for use by primary care providers. Over 30 million Americans have diabetes, and diabetic retinopathy--which occurs when blood sugar levels result in damage to retinal blood vessels--is considered mostly preventable. Still, it causes vision loss in tens of thousands of people each year and is the leading cause of blindness among working-age Americans. "Many patients with diabetes are not adequately screened for diabetic retinopathy since about 50 percent of them do not see their eye doctor on a yearly basis," Malvina Eydelman, MD, said in the FDA's official announcement. She serves as director of the Division of Ophthalmic, and Ear, Nose and Throat Devices at the agency's Center for Devices and Radiological Health.