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Artificial intelligence at the national eye institute
Noha A Sherif1, Emily Y Chew1, Michael F Chiang1
1National Eye Institute, National Institutes of Health, Bethesda, Maryland.
Current Opinion in Ophthalmology
|October 7, 2022
Summary
Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are advancing ophthalmology research, with initiatives from the National Institutes of Health (NIH) and National Eye Institute (NEI) focusing on early disease detection and improved patient outcomes.
Area of Science:
- Ophthalmology
- Biomedical Research
- Artificial Intelligence
Background:
- Ophthalmology is a key area for AI-driven biomedical innovation.
- Technological advancements enable linking vast datasets for scientific discovery.
Purpose of the Study:
- To review National Institutes of Health (NIH) and National Eye Institute (NEI) initiatives in artificial intelligence (AI), machine learning (ML), and deep learning (DL).
- To align with the NEI Strategic Plan and identify future opportunities in ophthalmology.
Main Methods:
- Review of NIH and NEI supported AI/ML/DL initiatives.
- Analysis of strategic plans for data science and ophthalmology.
Main Results:
- AI innovations show promise for early ocular disease detection, progression prediction, and quality of life improvements.
- There is a critical need for machine-actionable data collection, harmonization, and sharing.
- Ensuring health and research equity requires diverse data and workforces.
Conclusions:
- NIH/NEI actively support AI innovations to advance biomedical research in ophthalmology.
- Strategic plans outline activities to achieve AI-driven research goals.
- Initiatives are in place to facilitate AI research in the field.
