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20242026
most citedEnhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

q-bio.QM2026

Prediction bias in biological ageing markers

Yiqun Lin, Ariel Yuhan Ong, Matthew Yu Heng Wong +52

Biological ageing markers have attracted growing interest, with models estimating age from organ imaging or blood biomarkers. An estimated age above chronological age or the age-sp…

cs.CV2026

Enhancing Medical Visual Grounding via Knowledge-guided Spatial Prompts

Yifan Gao, Tao Zhou, Yi Zhou +3

Medical Visual Grounding (MVG) aims to identify diagnostically relevant phrases from free-text radiology reports and localize their corresponding regions in medical images, providi…

cs.CV2025

FusionFM: Fusing Eye-specific Foundational Models for Optimized Ophthalmic Diagnosis

Ke Zou, Jocelyn Hui Lin Goh, Yukun Zhou +11

Foundation models (FMs) have shown great promise in medical image analysis by improving generalization across diverse downstream tasks. In ophthalmology, several FMs have recently…

cs.CV2025

Clinician-Friendly Foundation Models for Ophthalmic Image Diagnostics without Fine-Tuning or Technical Barriers

Meng Wang, Tian Lin, Qingshan Hou +69

Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, yet most current models require retraining when applied across different clinical settings,…

cs.CV2025

Are Traditional Deep Learning Model Approaches as Effective as a Retinal-Specific Foundation Model for Ocular and Systemic Disease Detection?

Samantha Min Er Yew, Xiaofeng Lei, Jocelyn Hui Lin Goh +26

Background: RETFound, a self-supervised, retina-specific foundation model (FM), showed potential in downstream applications. However, its comparative performance with traditional d…

eess.IV2024

Enhancing Diagnostic Reliability of Foundation Model with Uncertainty Estimation in OCT Images

Yuanyuan Peng, Aidi Lin, Meng Wang +10

Inability to express the confidence level and detect unseen classes has limited the clinical implementation of artificial intelligence in the real-world. We developed a foundation…

eess.IV2024★ 1 cited

Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model

Meng Wang, Tian Lin, Aidi Lin +46

Previous foundation models for fundus images were pre-trained with limited disease categories and knowledge base. Here we introduce a knowledge-rich vision-language model (RetiZero…