Rethinking scale in ophthalmic artificial intelligence: from bigger models to smarter clinical reasoning
Abstract
Recent advances in ophthalmic AI have improved benchmark performance, yet clinical trust remains limited. We argue that progress should move beyond data and model scaling toward trustworthy, skill-efficient systems that integrate multimodal evidence, external knowledge, and uncertainty-aware reasoning. Ophthalmology provides a strong testbed for agentic AI, but safe clinical translation will require rigorous validation, workflow integration, and evaluation frameworks aligned with real-world decision making.
Fields of Study & Subjects
Clinical Reasoning and Diagnostic Skills
Artificial Intelligence in Healthcare and Education
Retinal Imaging and Analysis
Publication details
- Journal / source
- npj Digital Medicine
- Publisher
- Springer Science and Business Media LLC
- Volume
- 9
- Issue
- 1
- Publication date
- 9 May 2026
- Language
- EN