An international coalition of eye researchers used machine learning to develop classification criteria for 25 of the most common types of uveitis, a collection of over 30 diseases characterized by inflammation inside the eye. Together, these diseases are the fifth leading cause of blindness in the United States. The Standardization of Uveitis Nomenclature (SUN) Working Group, funded by the National Eye Institute (NEI), published its classification criteria in the American Journal of Ophthalmology. NEI is part of the National Institutes of Health.
“In the past, clinical research in the field of uveitis has been hampered by the lack of widely-accepted and validated diagnostic criteria,” said Douglas A. Jabs, M.D., M.B.A., the SUN project leader and professor of epidemiology and ophthalmology, Johns Hopkins Bloomberg School of Public Health, Baltimore. “These classification criteria are a major step forward for epidemiological studies, translational studies, pathogenesis research, outcomes research, and clinical trials. They hopefully will yield better disease-specific approaches to diagnosis and treatment.”