collaborators

10 papers

cs.AI2026

Beyond Prompt-Based Planning: MCP-Native Graph Planning-based Biomedical Agent System

Zhangtianyi Chen, Florensia Widjaja, Wufei Dai +3

Biomedical agents promise to automate complex biological workflows, yet current systems face two fundamental bottlenecks: bioinformatics tools are highly heterogeneous in interface…

cs.AI2026

MedGuideX: Internalizing Decision Logic from Executable Guidelines into Large Language Models for Clinical Reasoning

Yuhao Shen, Lang Cao, Simo Du +4

Clinical practice guidelines (CPGs) encode evidence-based decision logic that clinicians apply by evaluating patient variables, conditional criteria, and recommendation rules. Howe…

cs.CV2026

SkinGPT-X: A Self-Evolving Collaborative Multi-Agent System for Transparent and Trustworthy Dermatological Diagnosis

Zhangtianyi Chen, Yuhao Shen, Florensia Widjaja +6

While recent advancements in Large Language Models have significantly advanced dermatological diagnosis, monolithic LLMs frequently struggle with fine-grained, large-scale multi-cl…

cs.CV2026

Trustworthy and Fair SkinGPT-R1 for Democratizing Dermatological Reasoning across Diverse Ethnicities

Yuhao Shen, Zhangtianyi Chen, Yuanhao He +14

The clinical translation of dermatological AI is hindered by opaque reasoning and systematic performance disparities across skin tones. Here we present SkinGPT-R1, a multimodal lar…

cs.CV2026

A Vision-Language Foundation Model for Zero-shot Clinical Collaboration and Automated Concept Discovery in Dermatology

Siyuan Yan, Xieji Li, Dan Mo +28

Medical foundation models have shown promise in controlled benchmarks, yet widespread deployment remains hindered by reliance on task-specific fine-tuning. Here, we introduce DermF…

cs.DB2026

Honesty-Aware Multi-Agent Framework for High-Fidelity Synthetic Data Generation in Digital Psychiatric Intake Doctor-Patient Interactions

Xinyuan Zhang, Zijian Wang, Chang Dao +1

Data scarcity and unreliable self-reporting -- such as concealment or exaggeration -- pose fundamental challenges to psychiatric intake and assessment. We propose a multi-agent syn…