Isdin Oke, Tobias Elze, Joan W Miller, Alice C Lorch, Mei-Sing Ong, Ann Chen Wu, David G Hunter
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Using machine learning to identify pediatric ophthalmologists.
This cross-sectional study used data from the American Academy of Ophthalmology IRIS Registry (Intelligent Research in Sight) and machine learning algorithms to identify pediatric ophthalmologists based on physician coding patterns. A random forest model achieved an area under the receiver operating characteristic curve of 0.98, sensitivity of 0.98, and specificity of 0.88 when classifying pediatric eye specialists in the test validation cohort. Algorithm-based approaches to identify pediatric ophthalmologists using procedure codes may offer new avenues to determine the scope, scale, and trajectory of pediatric eye care delivery.
期刊介绍:
Journal of AAPOS presents expert information on children''s eye diseases and on strabismus as it affects all age groups. Major articles by leading experts in the field cover clinical and investigative studies, treatments, case reports, surgical techniques, descriptions of instrumentation, current concept reviews, and new diagnostic techniques. The Journal is the official publication of the American Association for Pediatric Ophthalmology and Strabismus.