Personalised Monitoring of Early and Intermediate Age-related Macular Degeneration With Artificial Intelligence and Identification of Disea…
The study is a prospective, multinational, multicenter observational trial that follows patients with early and intermediate age‑related macular degeneration (AMD) over 24 months to predict conversion to advanced AMD. It uses routine imaging modalities—scanning laser fundus photography, color fundus photography, optical coherence tomography, and OCT angiography—to identify focal and global retinal changes and assess individual risk of progression. Artificial intelligence is employed to enhance AMD classification alongside traditional models, with no intervention performed during the study per…
The study is a prospective, multinational, multicenter observational trial that follows patients with early and intermediate age‑related macular degeneration (AMD) over 24 months to predict conversion to advanced AMD. It uses routine imaging modalities—scanning laser fundus photography, color fundus photography, optical coherence tomography, and OCT angiography—to identify focal and global retinal changes and assess individual risk of progression. Artificial intelligence is employed to enhance AMD classification alongside traditional models, with no intervention performed during the study per…
This study demonstrates the potential for AI‑driven classification of AMD, a capability that Swiss AI researchers and institutions can build upon to improve early detection and personalized care.
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