activity
20242026
collaborators

7 papers

cs.HC2026

EyeAgent: An Agentic AI System for Multimodal Clinical Decision Support in Ophthalmology

Danli Shi, Xiaolan Chen, Bingjie Yan +24

Artificial intelligence has shown promise in medical imaging, yet most existing systems lack flexibility, interpretability, and adaptability - challenges especially pronounced in o…

cs.CV2025

Benchmarking Large Multimodal Models for Ophthalmic Visual Question Answering with OphthalWeChat

Pusheng Xu, Xia Gong, Xiaolan Chen +7

Purpose: To develop a bilingual multimodal visual question answering (VQA) benchmark for evaluating VLMs in ophthalmology. Methods: Ophthalmic image posts and associated captions p…

eess.IV2025

Predicting Diabetic Macular Edema Treatment Responses Using OCT: Dataset and Methods of APTOS Competition

Weiyi Zhang, Peranut Chotcomwongse, Yinwen Li +15

Diabetic macular edema (DME) significantly contributes to visual impairment in diabetic patients. Treatment responses to intravitreal therapies vary, highlighting the need for pati…

cs.CL2025

DeepSeek-R1 Outperforms Gemini 2.0 Pro, OpenAI o1, and o3-mini in Bilingual Complex Ophthalmology Reasoning

Pusheng Xu, Yue Wu, Kai Jin +3

Purpose: To evaluate the accuracy and reasoning ability of DeepSeek-R1 and three other recently released large language models (LLMs) in bilingual complex ophthalmology cases. Meth…

eess.IV2024

EyeDiff: text-to-image diffusion model improves rare eye disease diagnosis

Ruoyu Chen, Weiyi Zhang, Bowen Liu +5

The rising prevalence of vision-threatening retinal diseases poses a significant burden on the global healthcare systems. Deep learning (DL) offers a promising solution for automat…

eess.IV2024

Visual Question Answering in Ophthalmology: A Progressive and Practical Perspective

Xiaolan Chen, Ruoyu Chen, Pusheng Xu +4

Accurate diagnosis of ophthalmic diseases relies heavily on the interpretation of multimodal ophthalmic images, a process often time-consuming and expertise-dependent. Visual Quest…