9 citations · 31 across the 12 of their papers we have counts for
13 papers
EyeWorld: A Generative World Model of Ocular State and Dynamics
Ziyu Gao, Xinyuan Wu, Xiaolan Chen +10
Ophthalmic decision-making depends on subtle lesion-scale cues interpreted across multimodal imaging and over time, yet most medical foundation models remain static and degrade und…
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…
APTOS-2024 challenge report: Generation of synthetic 3D OCT images from fundus photographs
Bowen Liu, Weiyi Zhang, Peranut Chotcomwongse +23
Optical Coherence Tomography (OCT) provides high-resolution, 3D, and non-invasive visualization of retinal layers in vivo, serving as a critical tool for lesion localization and di…
ChatMyopia: An AI Agent for Pre-consultation Education in Primary Eye Care Settings
Yue Wu, Xiaolan Chen, Weiyi Zhang +7
Large language models (LLMs) show promise for tailored healthcare communication but face challenges in interpretability and multi-task integration particularly for domain-specific…
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…
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…
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…
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…
Fundus to Fluorescein Angiography Video Generation as a Retinal Generative Foundation Model
Weiyi Zhang, Jiancheng Yang, Ruoyu Chen +7
Fundus fluorescein angiography (FFA) is crucial for diagnosing and monitoring retinal vascular issues but is limited by its invasive nature and restricted accessibility compared to…
EyeCLIP: A visual-language foundation model for multi-modal ophthalmic image analysis
Danli Shi, Weiyi Zhang, Jiancheng Yang +8
Early detection of eye diseases like glaucoma, macular degeneration, and diabetic retinopathy is crucial for preventing vision loss. While artificial intelligence (AI) foundation m…
EyeFound: A Multimodal Generalist Foundation Model for Ophthalmic Imaging
Danli Shi, Weiyi Zhang, Xiaolan Chen +6
Artificial intelligence (AI) is vital in ophthalmology, tackling tasks like diagnosis, classification, and visual question answering (VQA). However, existing AI models in this doma…
Evaluating large language models in medical applications: a survey
Xiaolan Chen, Jiayang Xiang, Shanfu Lu +3
Large language models (LLMs) have emerged as powerful tools with transformative potential across numerous domains, including healthcare and medicine. In the medical domain, LLMs ho…
EyeGPT: Ophthalmic Assistant with Large Language Models
Xiaolan Chen, Ziwei Zhao, Weiyi Zhang +7
Artificial intelligence (AI) has gained significant attention in healthcare consultation due to its potential to improve clinical workflow and enhance medical communication. Howeve…