In-Context Learning for Data-Efficient Diabetic Retinopathy Detection via Multimodal Foundation Models

Objective: This study aims to evaluate whether in-context learning (ICL), a prompt-based learning mechanism enabling multimodal foundation models to rapidly adapt to new tasks without retraining or large annotated datasets, can achieve comparable diagnostic performance to domain-specific foundation...

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Ngā kaituhi matua:	Murat S. Ayhan, PhD, Ariel Y. Ong, MD, Eden Ruffell, Siegfried K. Wagner, MD, PhD, David A. Merle, MD, Pearse A. Keane, MD
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	Elsevier 2026-01-01
Rangatū:	Ophthalmology Science
Ngā marau:	AI Artificial intelligence Diabetic retinopathy Large language model LLM
Urunga tuihono:	http://www.sciencedirect.com/science/article/pii/S2666914525002325
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

In-Context Learning for Data-Efficient Diabetic Retinopathy Detection via Multimodal Foundation Models

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