Abstract
This paper provides a systematic survey of artificial intelligence (AI) models that have been proposed over the past decade to screen retinal diseases, which can cause severe visual impairments or even blindness. The paper covers both the clinical and technical perspectives of using AI models in hosipitals to aid ophthalmologists in promptly identifying retinal diseases in their early stages. Moreover, this paper also evaluates various methods for identifying structural abnormalities and diagnosing retinal diseases, and it identifies future research directions based on a critical analysis of the existing literature. This comprehensive study, which reviews both the conventional and state-of-the-art methods to screen retinopathy across different modalities, is unique in its scope. Additionally, this paper serves as a helpful guide for researchers who want to work in the field of retinal image analysis in the future.
| Original language | English |
|---|---|
| Article number | 111 |
| Number of pages | 93 |
| Journal | Artificial Intelligence Review |
| Volume | 57 |
| Early online date | 5 Apr 2024 |
| DOIs | |
| Publication status | Published - 5 Apr 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Keywords
- Age-related macular degeneration (AMD)
- Artificial intelligence
- Diabetic retinopathy (DR)
- Fundus
- Glaucoma
- Optical coherence tomography (OCT)
Fingerprint
Dive into the research topics of 'A comprehensive review of artificial intelligence models for screening major retinal diseases'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver