Data Sheet 1_A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema.docx
Version 1PurposeTo develop a machine learning model to predict anatomical response to anti-VEGF therapy in patients with diabetic macular edema (DME).MethodsThis retrospective study included patients with DME who underwent intravitreal anti-VEGF treatment between January 2023 and February 2025. Baseline data included optical coherence tomography (OCT) features and blood-based metabolic and hematologic markers. The primary outcome was defined as a ≥20% reduction in central retinal thickness (CRT) post-tre
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PurposeTo develop a machine learning model to predict anatomical response to anti-VEGF therapy in patients with diabetic macular edema (DME).MethodsThis retrospective study included patients with DME who underwent intravitreal anti-VEGF treatment between January 2023 and February 2025. Baseline data included optical coherence tomography (OCT) features and blood-based metabolic and hematologic markers. The primary outcome was defined as a ≥20% reduction in central retinal thickness (CRT) post-tre