Author

L. Nakayama

2 papers indexed here

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#artificial intelligence Preprint Sep 2026

FOCUS: Benchmarking Retinal Model Generalization from Foundation Vision Encoders to Multimodal LLMs

Progress in AI-based retinal image analysis has advanced with foundation models, yet evaluating their reliability remains challenging. Performance reported on a single dataset does not capture how models behave under dataset shift, across clinical definitions, or for different patient subgroups. This limitation is part...

David S. Restrepo, Chen-Wei Wu, L. Nakayama et al. · 0 citations

Open access Sep 2026

Diabetic retinopathy screening using artificial intelligence: a comprehensive performance comparison on datasets from diverse populations and imaging modalities

Objective. Diabetic retinopathy (DR) is the leading cause of preventable blindness in adults and poses significant challenges in low- and middle-income regions due to limited access to skilled clinicians and diagnostic facilities. Automated screening solutions using artificial intelligence (AI) have emerged as an effic...

Philipp Schapotschnikow, Vladyslav Dusiak, Murat Osswald et al. · Physiological Measurement · 0 citations