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AI in Neuro-Ophthalmology: Current Practice and Future Opportunities
Rachel C Kenney1, Tim W Requarth, Alani I Jack
1Departments of Neurology (RCK, AJ, SH, SG, SNG), Population Health (RCK), and Ophthalmology (SG), New York University Grossman School of Medicine, New York, New York; and Vilcek Institute of Graduate Biomedical Sciences (TR), New York University Grossman School of Medicine, New York, New York.
Artificial intelligence (AI) offers innovative solutions for neuro-ophthalmology, improving diagnostic accuracy and efficiency. AI integration promises to enhance patient care and access to specialized resources despite current challenges.
Area of Science:
- Neuro-ophthalmology
- Artificial Intelligence
- Medical Imaging
Background:
- Neuro-ophthalmology diagnosis is complex, time-intensive, and requires specialized expertise.
- Shortage of neuro-ophthalmologists necessitates efficient diagnostic solutions.
- Artificial intelligence (AI) shows potential in interpreting imaging data and aiding diagnosis.
Purpose of the Study:
- To provide a comprehensive overview of AI applications in neuro-ophthalmology.
- To explore AI's role in disease progression prediction using OCT and fundus photography.
- To examine the integration of generative AI in neuro-ophthalmic education and practice.
Main Methods:
- Conducted electronic literature searches using PubMed and Google Scholar.
- Performed a comprehensive search within the Journal of Neuro-Ophthalmology.
- Included terms: AI, machine learning, deep learning, natural language processing, computer vision, large language models, and generative AI.
Main Results:
- AI applications are diverse, including predictive modeling for disease progression.
- AI, OCT, and fundus photography are key areas of development.
- Generative AI is being explored for educational and clinical integration.
Conclusions:
- AI has a transformative potential impact on neuro-ophthalmology practice and research.
- AI can improve diagnostic accuracy and identify novel therapeutic interventions.
- AI may enhance access to subspecialty resources while addressing integration challenges.
