ArticleGraefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie2026
Reduced AI-based sex classification performance in clinically unaffected fellow eyes of patients with polypoidal choroidal vasculopathy: comparison with central serous chorioretinopathy and controls.
Article in Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeTo compare AI-based biological-sex classification in control eyes and clinically unaffected fellow eyes of patients with central serous chorioretinopathy (CSC) or polypoidal choroidal vasculopathy (PCV).
methodsThis retrospective exploratory study included one eye per participant (82 controls, 48 CSC fellow eyes, and 61 PCV fellow eyes). A publicly released Japan Ocular Imaging Registry EfficientNet-B7 model classified sex from JPEG color fundus photographs using a prespecified female-probability threshold of 0.5. Accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and Cohen's kappa were estimated. Logistic regression was adjusted for age and biological sex and was kept parsimonious because only 32 misclassification events occurred; Firth penalized logistic regression was performed as a sensitivity analysis.
resultsAccuracy was 89.0% (95% confidence interval [CI], 80.4-94.1%) in controls, 87.5% (75.3-94.1%) in CSC fellow eyes, and 72.1% (59.8-81.8%) in PCV fellow eyes (overall p = 0.018). Accuracy was lower for PCV fellow eyes than for controls (Bonferroni-adjusted p = 0.045); the CSC-PCV comparison was not significant (adjusted p = 0.183). AUCs were 0.935, 0.879, and 0.715, respectively. PCV was associated with misclassification after adjustment for age and biological sex (odds ratio [OR], 3.13; 95% CI, 1.23-8.00; p = 0.017), with a similar Firth estimate (OR, 2.97; 95% CI, 1.22-7.69; p = 0.017).
conclusionAI-based sex classification was less accurate in clinically unaffected PCV fellow eyes than in controls, whereas performance in CSC fellow eyes was comparable to controls. Because the groups were unmatched, only 32 misclassification events occurred, and imaging-related confounding could not be fully assessed, these findings are hypothesis-generating.
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