Publications (6)
Knowledge-augmented Agentic AI for Mental Health Medication Information Seeking
Huizi Yu, Jian Liu, Wenkong Wang +10
Patients increasingly seek medication information online, yet safety knowledge for psychiatric drugs is split between regulatory adverse-event records, which are authoritative but…
Evaluating an evidence-guided reinforcement learning framework in aligning light-parameter large language models with decision-making cognition in psychiatric clinical reasoning
Xinxin Lin, Guangxin Dai, Yi Zhong +20
Large language models (LLMs) hold transformative potential for medical decision support yet their application in psychiatry remains constrained by hallucinations and superficial re…
DispatchMAS: Fusing taxonomy and artificial intelligence agents for emergency medical services
Xiang Li, Huizi Yu, Wenkong Wang +17
Objective: Emergency medical dispatch (EMD) is a high-stakes process challenged by caller distress, ambiguity, and cognitive load. Large Language Models (LLMs) and Multi-Agent Syst…
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
Does Learning Mathematical Problem-Solving Generalize to Broader Reasoning?
Ruochen Zhou, Minrui Xu, Shiqi Chen +5
There has been a growing interest in enhancing the mathematical problem-solving (MPS) capabilities of large language models. While the majority of research efforts concentrate on c…
AIPatient Arena: EHR-grounded evaluation of large language models in end-to-end clinical consultation workflows
Jiahui Niu, Huizi Yu, Wenkong Wang +11
Large language models (LLMs) are increasingly considered for use in clinical consultation tasks, yet most medical evaluations remain static, single-turn, or narrowly outcome-based,…