Artificial Intelligence in Ophthalmology: A New Era for Retinal Disease Detection and Treatment
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Neurobiology".
Deadline for manuscript submissions: closed (31 March 2026) | Viewed by 835
Special Issue Editor
Interests: photoreceptor degeneration; retinal development; retinal gene therapy
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The integration of artificial intelligence (AI) into retinal disease research has transformed not only clinical diagnosis but also molecular and pathological investigations. AI-powered image analysis enables automated detection and classification of retinal diseases such as diabetic retinopathy, age-related macular degeneration, and glaucoma from high-resolution imaging data, including optical coherence tomography (OCT) and fundus photographs. Beyond imaging, AI is increasingly applied to molecular datasets such as transcriptomics, proteomics, and metabolomics, allowing researchers to identify disease-related biomarkers and molecular pathways with unprecedented precision. In pathological research, deep learning models can quantify cellular and tissue-level alterations in histological samples, facilitating objective assessment of retinal degeneration and inflammation. By integrating clinical, molecular, and pathological data, AI provides a comprehensive understanding of disease mechanisms and progression. Ultimately, this multidisciplinary approach holds great promise for early detection, personalized treatment, and the discovery of novel therapeutic targets for retinal disorders.
Prof. Dr. Hiroshi Tomita
Guest Editor
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Keywords
- artificial intelligence
- retina
- imaging
- transcriptome analysis
- protein modeling
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