Hyeokjong Lee

Abstract Widespread screening of anaemia is currently limited by the need for invasive blood tests. This study’s primary objective was to evaluate the feasibility and interpretability of Vision Transformer (ViT)-based foundation models, including those pretrained on natural or medical domains, for the noninvasive estimation of haemoglobin (Hb) levels using retinal fundus images.

Abstract Dementia is a growing global health challenge, and early identification is essential for timely intervention. We evaluated whether foundation model–based deep learning of retinal fundus photographs can detect dementia and predict future dementia incidence. Using health checkup data from over 36,000 Korean individuals, dementia was defined by diagnosis with relevant medication. Five vision foundation models were assessed with multiple fine-tuning strategies.