Application of Artificial Intelligence in Ophthalmology: An Updated Comprehensive Review.

Hashemian, Hesam; Peto, Tunde; Ambrósio, Renato; Lengyel, Imre; Kafieh, Rahele; Muhammed Noori, Ahmed; Khorrami-Nejad, Masoud

Abstract

Artificial intelligence (AI) holds immense promise for transforming ophthalmic care through automated screening, precision diagnostics, and optimized treatment planning. This paper reviews recent advances and challenges in applying AI techniques such as machine learning and deep learning to major eye diseases. In diabetic retinopathy, AI algorithms analyze retinal images to accurately identify lesions, which helps clinicians in ophthalmology practice. Systems like IDx-DR (IDx Technologies Inc, USA) are FDA-approved for autonomous detection of referable diabetic retinopathy. For glaucoma, deep learning models assess optic nerve head morphology in fundus photographs to detect damage. In age-related macular degeneration, AI can quantify drusen and diagnose disease severity from both color fundus and optical coherence tomography images. AI has also been used in screening for retinopathy of prematurity, keratoconus, and dry eye disease. Beyond screening, AI can aid treatment decisions by forecasting disease progression and anti-VEGF response. However, potential limitations such as the quality and diversity of training data, lack of rigorous clinical validation, and challenges in regulatory approval and clinician trust must be addressed for the widespread adoption of AI. Two other significant hurdles include the integration of AI into existing clinical workflows and ensuring transparency in AI decision-making processes. With continued research to address these limitations, AI promises to enable earlier diagnosis, optimized resource allocation, personalized treatment, and improved patient outcomes. Besides, synergistic human-AI systems could set a new standard for evidence-based, precise ophthalmic care.

Citation

Hashemian, H., Peto, T., Ambrósio, R., Lengyel, I., Kafieh, R., Muhammed Noori, A., & Khorrami-Nejad, M. (2024). Application of Artificial Intelligence in Ophthalmology: An Updated Comprehensive Review. Journal of Ophthalmic and Vision Research, 19(3), 354-367. https://doi.org/10.18502/jovr.v19i3.15893

• Journal Article Type: Article
• Acceptance Date: Jul 6, 2024
• Online Publication Date: Sep 16, 2024
• Publication Date: Sep 16, 2024
• Deposit Date: Oct 23, 2024
• Publicly Available Date: Oct 23, 2024
• Journal: Journal of Ophthalmic and Vision Research
• Electronic ISSN: 2008-322X
• Publisher: Knowledge E
• Peer Reviewed: Peer Reviewed
• Volume: 19
• Issue: 3
• Pages: 354-367
• DOI: https://doi.org/10.18502/jovr.v19i3.15893
• Keywords: Screening, Treatment, Ophthalmology, Artificial Intelligence, Prognosis
• Public URL: https://durham-repository.worktribe.com/output/2977467