Artificial intelligence oculomics for systemic health and longevity medicine: 2025 and beyond
Artificial intelligence applied to retinal imaging has matured from proof-of-concept classifiers to externally validated, occasionally regulated tools that noninvasively profile systemic conditions. Multiplexed foundation models and multimodal transformers herald a shift toward holistic 'oculomics' platforms, yet prospective multicenter trials, equitable performance auditing, and health-economic evaluations are essential before widescale clinical adoption.
Authors
- Daniel Shu Wei Ting (ORCID: https://orcid.org/0000-0003-2264-7174)
- Jie Yao (ORCID: https://orcid.org/0000-0002-8325-166X)
- Ashley Shuen Ying Hong (ORCID: https://orcid.org/0009-0003-2347-3986)
- Kanae Fukutsu
Institutions
- Singapore National Eye Center (SG)
- Singapore Eye Research Institute (SG)
- Duke-NUS Medical School (SG)
- Smith-Kettlewell Eye Research Institute (US)
- Artificial Intelligence in Medicine (Canada) (CA)
Publication Details
- Journal
- Current Opinion in Ophthalmology
- Published
- 2025-09-03
- DOI
- https://doi.org/10.1097/icu.0000000000001174
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00