Machine-Learning Models Predict Two-Year VA Outcomes of Anti-VEGF Therapy
By Lynda Seminara
Selected by Andrew P. Schachat, MD
In a secondary analysis of responses to anti-VEGF treatment in the Comparison of Age-Related Macular Degeneration (AMD) Treatments Trials (CATT), Chandra et al. used robust data to develop and validate machine-learning (ML) models, with the goal of predicting the two-year VA outcomes of anti-VEGF therapy for patients with neovascular AMD (nAMD).