Application of Artificial Intelligence to Quantitative Assessment of Fundus Tessellated Density in Young Adults with Different Refractions

Research Article

Open Access Gateway Runkuan L. · Xiaoxiao G. · Zhang X. · Xiuzhen L. · Wu Q. · Tian Q. · Guo B. · Xu J. · Guodong T. · Jiaojiao F. · Lili Z. · Saiguang L. · Zhou D. · Jike S. · Bi H.
Abstract

Abstract Introduction: To quantitatively assess fundus tessellated density (FTD) and associated factors by artificial intelligence (AI) in young adults. Methods: A total of 1084 undergraduates (age, 17-23 years old) were enrolled in November 2021. The students were divided into three groups according to axial length (AL): Group 1 (AL

The Author(s). Published by S. Karger AG, Basel

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