Highlight
- Ellipsoid zone (EZ) integrity metrics and hyperreflective foci (HRF) counts are strong baseline predictors of intermediate AMD progression to advanced atrophic AMD over 2 years.
- Machine learning-enhanced quantitative OCT analysis effectively identifies subtle retinal structural changes not apparent on conventional imaging.
- A predictive random forest model using multiple OCT biomarkers achieved high accuracy (AUC = 0.85) in forecasting disease progression.
- These findings underscore the potential for early risk stratification, informing clinical trial design and targeted therapeutic interventions to delay atrophic AMD onset.
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For clinical reference; use professional judgment.

