(HealthDay)—A brand new synthetic intelligence algorithm can predict risk for age-related macular degeneration (AMD), in keeping with a research revealed within the April concern of Translational Vision Science and Technology.
Alauddin Bhuiyan, Ph.D., from iHealthScreen Inc. in New York City, and colleagues used 116,875 colour fundus photographs from 4,139 contributors of the Age-related Eye Disease Study to develop a machine studying method that may predict risk for development to late AMD inside one or two years. This model, which incorporates sociodemographic and clinical data, was validated utilizing information from the Nutritional AMD Treatment-2 (NAT-2) research.
The researchers discovered that for identification of early/none versus intermediate/late (e.g., referral stage) AMD, the model achieved 99.2 p.c accuracy. Overall, for a two-year incidence of late AMD (any), the prediction model achieved 86.36 p.c accuracy, with 66.88 p.c for late dry AMD and 67.15 p.c for late moist AMD. Using information from the NAT-2 research, the two-year late AMD prediction accuracy was 84 p.c.
“Validated color fundus photo-based models for AMD screening and risk prediction for late AMD are now ready for clinical testing and potential telemedical deployment,” the authors write.
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AI model predicts risk for age-related macular degeneration (2020, May 27)
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