Artificial Intelligence in Eye Disease, 3rd Edition
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 12912
Special Issue Editor
2. Department of Artificial Intelligence, Korea University, Seoul 136-701, Republic of Korea
Interests: artificial intelligence in biomedicine; diagnosis of retinal diseases; deep learning for ophthalmology images; neuroscience research
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
While the use of artificial intelligence (AI) is rapidly spreading to the medical world amid the vortex of the Fourth Industrial Revolution, the use of AI in ophthalmology is attracting attention for the diagnosis of various ophthalmic diseases, including optic nerve diseases, which are difficult to diagnose. In particular, introducing AI could help to diagnose with high accuracy when applied to fundus photographs, optical coherence tomography, and the visual field to achieve strong classification performance in the detection of occular and retinal diseases. In occular imaging, AI can be used as a possible solution for screening, diagnosing, and monitoring patients with major eye diseases in primary care and community settings. For instance, through deep learning algorithms that read retinal images, various diseases can be observed, such as bleeding, macular abnormalities—e.g., drusen—choroidal abnormalities, retinal vessel abnormalities, nerve fiber layer defects, and glaucomatous optic nerve papilla changes. Thus, deep learning architectures can be applied to learn to recognize eye diseases, thereby raising the diagnosis rate with a clinically acceptable performance. In other words, AI serves as a safety device for both patients and doctors, as well as an auxiliary tool to quickly judge the results. It prevents the possibility of misdiagnosis that can occur in the first place, provides treatment efficiency, and increases patient reliability. Consequently, AI could potentially revolutionize the way that ophthalmology is practiced in the future. Thus, the aim of this Special Issue is to highlight the recent progress and trends in utilizing AI techniques, such as machine learning and deep learning for detecting, screening, diagnosing, and monitoring numerous eye diseases, not only in diverse clinical practice but also in basic research on ophthalmology.
Prof. Dr. Jae-Ho Han
Guest Editor
Manuscript Submission Information
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Keywords
- medical diagnosis
- artificial intelligence
- deep learning
- fundus image
- optical coherence tomography
- ophthalmology
- retinal vessel
- glaucoma
- retinopahty
- macular degeneration
- image segmentation
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Related Special Issues
- Artificial Intelligence in Eye Disease in Diagnostics (12 articles)
- Artificial Intelligence in Eye Disease – Volume 2 in Diagnostics (10 articles)