AGE-RELATED MACULAR DEGENERATION CURRENT INVESTIGATIONS AND TREATMENTS

agerelatedmaculardeg774enerationkapak

ARTIFICIAL INTELLIGENCE AND DEEP LEARNING IN AGE-RELATED MACULAR DEGENERATION DIAGNOSIS

Furkan Emre Söğüt

Halil Şıvgın Çubuk State Hospital, Department of Ophthalmology, Ankara, Türkiye

Söğüt FE. Artificial Intelligence and Deep Learning in Age-Related Macular Degeneration Diagnosis. In: Çıtırık M, Şekeryapan Gediz B, editors. Age-Related Macular Degeneration: Current Investigations and Treatments. 1st ed. Ankara: Türkiye Klinikleri; 2025. p.87-93.

ABSTRACT

Age-related macular degeneration (AMD) stands as the leading cause of irreversible vision loss among individuals aged 50 and above, with a projected global prevalence exceeding 288 million cases by 2040. Artificial intelligence (AI) and deep learning technologies have emerged as innovative solutions in AMD diagnosis. These technologies automate image analysis, delivering objective and reproducible diagnostic insights, and have demonstrated remarkable accuracy in identifying AMD-related features such as drusen, retinal pigment epithelium (RPE) changes and choroidal neovascularization. AI-driven tools also contribute to risk stratification, enabling earlier detection and personalized treatment strategies. This article aims to elucidate the impact of artificial intelligence and machine learning on the diagnosis and management of age-related macular degeneration.

Keywords: Age related macular degeneration; Artificial intelligence; Deep learning; Retinal diseases; Retinal drusen

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