AI has 100% detection rate of blindness-causing condition

New artificial intelligence technology has shown a 100% success rate in identifying severe cases of a blindness-causing condition that affects prematurely born babies, according to new research from Oregon Health & Science University and collaborators, published in the journal JAMA Ophthalmology. JAMA Ophthalmology. 

The screening technology could lead to  sight-saving treatment for retinopathy of prematurity, the condition that caused musician Stevie Wonder to go blind, according to a March 7 press release from Oregon Health & Science University. 

About 2 million babies annually are born early enough to develop ROP, but in most cases the disease is mild and resolves without treatment. Severe cases cause about 500 babies in the U.S. and about 50,000 babies globally to go blind every year. 

The majority of cases that go untreated are in low- or middle-income communities. The AI algorithm was developed by Michael Chiang, MD, now director of the National Eye Institute of the National Institutes of Health. 

For the study, the AI system analyzed nearly 12,000 images of more than 4,000 babies' retinas. The photos were taken by nurses at neonatal intensive care units in U.S. and Indian hospitals. 

Ophthalmologists had previously reviewed the images as part of telemedicine programs in both countries and found that about 1.2% of the babies had severe forms of ROP, while about 5.8% had more-than-mild cases. The AI system correctly identified all of the severe cases and accurately detected 80% of the cases with more-than-mild ROP.

The AI technology is not yet available for clinical practice, but the results suggest it could be an effective screening tool for ROP telemedicine programs, the study said. 

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