The incorporation of Large Language Models (LLMs) in healthcare marks a
significant advancement. However, the application has predominantly been
limited to discriminative and question-answering tasks, which does not fully
leverage their interactive potential. To address this limitation, our paper
presents AI Hospital, a framework designed to build a real-time interactive
diagnosis environment. To simulate the procedure, we collect high-quality
medical records to create patient, examiner, and medical director agents. AI
Hospital is then utilized for the interactive evaluation and collaboration of
LLMs. Initially, we create a Multi-View Medical Evaluation (MVME) benchmark
where various LLMs serve as intern doctors for interactive diagnosis.
Subsequently, to improve diagnostic accuracy, we introduce a collaborative
mechanism that involves iterative discussions and a dispute resolution process
under the supervision of the medical director. In our experiments, we validate
the reliability of AI Hospital. The results not only explore the feasibility of
apply LLMs in clinical consultation but also confirm the effectiveness of the
dispute resolution focused collaboration method.

大型语言模型（LLMs）在医疗保健领域的应用具有重要意义，为了充分利用其交互潜力，本文提出了 AI Hospital 框架，用于构建实时互动诊断环境，并通过多视角医学评估（MVME）基准和协作机制来验证其可行性和有效性。