Communications of the ACM
Computer Diagnoses Cataracts as Well as Eye Doctors Can
Scientists at Sun Yat-Sen University in China are using a new artificial neural network to recognize and diagnose congenital cataracts as accurately as eye doctors.
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Scientists at Sun Yat-Sen University in China are using a new artificial neural network called CC-Cruiser to recognize and diagnose congenital cataracts as accurately as eye doctors.
CC-Cruiser is a convolutional neural network, which was trained on images from the Childhood Cataract Program of the Chinese Ministry of Health. CC-Cruiser was then given unlabeled data from 57 patients, including 43 with normal eyes and 14 with cataracts. The network identified cases of congenital cataracts with 98.25% accuracy, estimated the location of cataracts with 100-percent accuracy, and suggested the proper treatment with 92.86% accuracy.
In a test using 13 images of normal eyes and 40 pictures of cataracts found on the Internet, CC-Cruiser was slightly less successful. Potential cases of congenital cataracts were identified with 92.45% accuracy, location was estimated with 94.87%accuracy, and proper treatment was suggested with 89.74% accuracy; this decline may have been due to the photographs' variations in lighting, angle, and resolution.
In a test comparing CC-Cruiser with ophthalmologists, the network identified all cases with congenital cataracts, while all three eye doctors missed one case.
The Sun Yat-Sen researchers say their technology could be adapted to work on other diseases that rely on diagnoses via medical imaging.
From Live Science
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