利用机器学习识别儿科眼科医生。

IF 1.2 4区 医学 Q3 OPHTHALMOLOGY Journal of Aapos Pub Date : 2024-11-19 DOI:10.1016/j.jaapos.2024.104052
Isdin Oke, Tobias Elze, Joan W Miller, Alice C Lorch, Mei-Sing Ong, Ann Chen Wu, David G Hunter
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引用次数: 0

摘要

这项横断面研究使用了美国眼科学会IRIS注册表(视力智能研究)的数据和机器学习算法,根据医生编码模式识别儿科眼科医生。随机森林模型对试验验证队列中的儿科眼科专家进行分类时,受试者工作特征曲线下面积为0.98,灵敏度为0.98,特异性为0.88。使用程序代码识别儿童眼科医生的基于算法的方法可能为确定儿童眼科护理交付的范围、规模和轨迹提供新的途径。
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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.

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来源期刊
Journal of Aapos
Journal of Aapos 医学-小儿科
CiteScore
2.40
自引率
12.50%
发文量
159
审稿时长
55 days
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.
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