Stanford researchers tackle diabetic eye disease with AI

A team of researchers from Stanford Health Care's Byers Eye Institute in Palo Alto, Calif., developed an artificial intelligence algorithm that detects diabetic retinopathy.

The researchers used 75,137 images of individuals with and without diabetic retinopathy to train a deep-learning algorithm to identify patients in need of medical referral, according to a study published in Ophthalmology.

The researchers determined the algorithm could identify all stages of the disease — from mild to severe — with 94 percent accuracy. Researchers hope the algorithm, which can run on a personal computer or smartphone, will support early diagnosis and intervention.

"What we showed is that an artificial intelligence-based grading algorithm can be used to identify, with high reliability, which patients should be referred to an ophthalmologist for further evaluation and treatment," said lead author Theodore Leng, MD. "If properly implemented on a worldwide basis, this algorithm has the potential to reduce the workload on doctors and increase the efficiency of limited healthcare resources."

More articles on health IT:
Accenture: Top 5 barriers to healthcare IoT adoption
Memorial Hermann agrees to $2.4M HIPAA settlement
Alphabet exec departs to head new mental health startup

© Copyright ASC COMMUNICATIONS 2020. Interested in LINKING to or REPRINTING this content? View our policies by clicking here.


Featured Webinars

Featured Whitepapers