Segmed Showcases Peer-Reviewed AI Cataract Study, Highlighting Strength in Real-World Medical Data

Segmed has shared an update. The company highlighted a newly published study in the Journal of Health Informatics, conducted in collaboration with the Brazilian Society of Health Informatics and academic partners, demonstrating the use of artificial intelligence to diagnose cataracts and guide surgical referrals using real-world clinical data. The AI models, trained on more than 2,600 eye images from a teleophthalmology program in Brazil, achieved 90.6% accuracy (ROC AUC 96.7%) for cataract diagnosis and 86.5% accuracy (ROC AUC 94.3%) for identifying patients needing referral for surgical evaluation. Segmed’s VP of Clinical Insights and Real-World Evidence is a co-author, underlining the company’s role in enabling AI development based on heterogeneous, real-world healthcare datasets.

For investors, this publication underscores Segmed’s positioning as an enabling infrastructure provider for medical AI rather than a direct care-delivery company. Demonstrated high-performance AI models built on real-world, diverse data validate the relevance of Segmed’s data-access and real-world evidence platform for healthcare AI developers, payers, and providers. Peer-reviewed evidence can strengthen Segmed’s credibility with pharmaceutical, medtech, and health system partners, potentially supporting deal flow, pricing power for data and analytics offerings, and long-term revenue growth. Moreover, the teleophthalmology use case highlights applicability in emerging markets and remote-care models, suggesting broader addressable market opportunities in digital health and clinical AI, although near-term financial impact is likely to depend on Segmed’s ability to convert this technical validation into commercial contracts and platform adoption.