collaborators

12 papers

cs.CV2026

UniMod: Enhancing Multi-Modal Medical Diagnosis through Cross-Modality and Within-Modality Alignment

Zijian Gu, Weikai Lin, Shuang Zhou +2

Multi-modal learning combining medical images and clinical text is promising for disease diagnosis. However, standard multi-modal training leads to shortcut learning: models exploi…

cs.CL2026

Let LLMs Judge Each Other: Multi-Agent Peer-Reviewed Reasoning for Medical Question Answering

Zaifu Zhan, Shuang Zhou, Rui Zhang

Objective: To enhance the accuracy, interpretability, and robustness of large language models (LLMs) in medical question answering (MedQA). Method: We designed a multi-agent peer-r…

cs.CL2026

OralMLLM-Bench: Evaluating Cognitive Capabilities of Multimodal Large Language Models in Dental Practice

Rongyang Wang, Shuang Zhou, Jiashuo Wang +2

Multimodal large language models (MLLMs) have emerged as a promising paradigm for dental image analysis. However, their ability to capture the multi-level cognitive processes requi…

cs.LG2026

PRIME: Prototype-Driven Multimodal Pretraining for Cancer Prognosis with Missing Modalities

Kai Yu, Shuang Zhou, Yiran Song +9

Multimodal self-supervised pretraining offers a promising route to cancer prognosis by integrating histopathology whole-slide images, gene expression, and pathology reports, yet mo…

cs.CL2026

EpiScreen: Early Epilepsy Detection from Electronic Health Records with Large Language Models

Shuang Zhou, Kai Yu, Zaifu Zhan +5

Epilepsy and psychogenic non-epileptic seizures often present with similar seizure-like manifestations but require fundamentally different management strategies. Misdiagnosis is co…

cs.CL2026

HeartAgent: An Autonomous Agent System for Explainable Differential Diagnosis in Cardiology

Shuang Zhou, Kai Yu, Song Wang +11

Heart diseases remain a leading cause of morbidity and mortality worldwide, necessitating accurate and trustworthy differential diagnosis. However, existing artificial intelligence…