Factors in Color Fundus Photographs That Can Be Used by Humans to Determine Sex of Individuals.

Translational Vision Science & Technology
Takehiro YamashitaTaiji Sakamoto

Abstract

Artificial intelligence (AI) can identify the sex of an individual from color fundus photographs (CFPs). However, the mechanism(s) involved in this identification has not been determined. This study was conducted to determine the information in CFPs that can be used to determine the sex of an individual. Prospective observational cross-sectional study of 112 eyes of 112 healthy volunteers. The following characteristics of CFPs were analyzed: the color of peripapillary area expressed by the mean values of red, green, and blue intensities, and the tessellation expressed by the tessellation fundus index (TFI). The optic disc ovality ratio, papillomacular angle, retinal artery trajectory, and retinal vessel angles were also quantified. Their differences between the sexes were assessed by Mann-Whitney U tests. Regularized binomial logistic regression was used to select the decisive factors. In addition, its discriminative performance was evaluated through the leave-one-out cross validation. The mean age of 76 men and 36 women was 25.8 years. The regularized binomial logistic regression delivered the optimal model for sex selected variables of peripapillary temporal green and blue intensities, temporal TFI, supratemporal TFI, optic d...Continue Reading

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Citations

Aug 25, 2020·Translational Vision Science & Technology·Simon DieckPeter M Krawitz
Jan 7, 2021·Translational Vision Science & Technology·Toon Van CraenendonckPatrick De Boever
Mar 7, 2021·Journal of Clinical Medicine·Hiroto TerasakiTaiji Sakamoto
May 15, 2021·Scientific Reports·Edward KorotPearse A Keane
Oct 17, 2020·Graefe's Archive for Clinical and Experimental Ophthalmology = Albrecht Von Graefes Archiv Für Klinische Und Experimentelle Ophthalmologie·Saki NomaTaiji Sakamoto

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