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

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.MA2026

MedCollab: IBIS-Guided Multi-Agent Collaboration with Hierarchical Disease Relation Chains for Clinical Diagnosis

Yuqi Zhan, Xinyue Wu, Tianyu Lin +6

Clinical diagnosis is a gradual process of evidence integration, in which physicians move from symptoms and medical history to examinations, competing hypotheses, disease relations…

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,…

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…