collaborators

5 papers

cs.CL2026

Are LLMs Ready to Assist Physicians? PhysAssistBench for Interactive Doctor-Patient-EHR Assistance

Tianming Du, Peijie Yu, Sihan Shang +12

The most plausible near-term role of medical LLMs is to assist rather than replace physicians, yet current evaluations often test isolated capabilities: clinical knowledge, EHR sys…

cs.CV2026

Evo-RAD: Navigating Rare Retinal Disease Diagnosis via Self-Evolving Agentic Retrieval

Wangding Xia, Ye Du, Jiashi Lin +3

Large-scale pretrained foundation models have revolutionized general medical screening, but often falter on rare diseases because such conditions are underrepresented in real-world…

cs.CV2026

GenMed: A Pairwise Generative Reformulation of Medical Diagnostic Tasks

Hantao Zhang, Weidong Guo, Yuhe Liu +5

Data-driven medical AI is traditionally formulated as a discriminative mapping from input to output via a learned function , which does not generalize well across hetero…

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.CV2024

OphCLIP: Hierarchical Retrieval-Augmented Learning for Ophthalmic Surgical Video-Language Pretraining

Ming Hu, Kun Yuan, Yaling Shen +17

Surgical practice involves complex visual interpretation, procedural skills, and advanced medical knowledge, making surgical vision-language pretraining (VLP) particularly challeng…