Data Sheet 1_Quantitative color fundus photography parameters as potential biomarkers of axial length progression: evidence from a machine learning cohort study.docx
Version 1PurposeEarly identification of children at risk for accelerated axial elongation is essential for implementing timely myopia control strategies. Quantitative parameters derived from color fundus photography (CFP) may capture subtle structural and microvascular features relevant to axial length (AL) progression, yet their predictive value remains insufficiently characterized. To develop and validate a machine learning–based model integrating CFP-derived quantitative biomarkers and clinical charac
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PurposeEarly identification of children at risk for accelerated axial elongation is essential for implementing timely myopia control strategies. Quantitative parameters derived from color fundus photography (CFP) may capture subtle structural and microvascular features relevant to axial length (AL) progression, yet their predictive value remains insufficiently characterized. To develop and validate a machine learning–based model integrating CFP-derived quantitative biomarkers and clinical charac