Remarkable advances in imaging, computation, and technology are rapidly moving us into an era where biomedical knowledge discovery is increasingly limited only by creativity. This has resulted in unprecedented opportunities to improve the diagnosis and treatment of disease. The vision field has been at the forefront of these advances in AI for healthcare because of the easy accessibility of images and clinical data.

This talk will discuss challenges and opportunities involving artificial intelligence and data science in ophthalmology research and applications to clinical care. Specific examples will be given from the speaker’s perspective as an investigator in this field and as Director of the National Eye Institute (NEI), which directs and funds vision research in the United States. This will include discussion of challenges in the accuracy and process of ophthalmic diagnosis, insights and gaps in knowledge regarding AI research in ophthalmology, and ways in which these challenges and opportunities are generalizable to other medical fields. It will conclude with discussion of current NEI priorities including data sharing, data harmonization, data generation, medical education in informatics and data science, methodological innovation, and population health.