基于Multi-Agents 分布式医学诊断系统研究

医学诊断系统是一个新兴的复杂的应用系统,人工智能技术,计算机协作支持技术及 高速通信网络体系结构的发展促进了计算机支持的诊断系统的发展．当前医学诊断系统的难 点在于如何利用网络这个资源分布平台来获取所需要的数据及在数据不完整状态进行推理求 解，而这些问题的解决在于能够有一种机制使得能在一个标准的应用系统结构中准确的表示 并获取信息及集成各种医学资源使之相互协作．本文描述了一种利用多智能体(Multi-agen ts system, MAS)体系结构和中间件(middleware)技术如公共请求代理结构(Common Object Request Broker Architecture, CORBA)进行设计的分布式医学诊断系统. 该系统能集成多 种医学资源和医学应用实体并且能实现参与诊断的医学实体之间的协作，以减少由于信息缺 乏而带来的诊断偏差. 另外本文还将一种实验室开发的模糊最小最大神经网络(Fuzzy Min- Max Neural Network, FMMNN)的模糊规则提取方法应用于该系统以证实该分布式诊断系统的 优越性.

STUDY OF MULTI-AGENTS DISTRIBUTED MEDICAL DIAGNOSIS SYSTEM

The medical diagnosis system is a new complicated application system. The development of some new technologies such as Artificial Intelligent (AI), Computer Supported Cooperative Work (CSCW), and high bandwidth architecture made computer supported medical diagnosis available. Now the difficulty of the medical diagnosis is how to utilize the network which is the distributed processing platform to acquire the needed data and to reason in the condition of lacking the relative information. One of methods for solving the problem is to design an efficient architecture to integrate medical resources and expert knowledge to made them collaborative work. This paper describes a distributed medical diagnosis system using Multi-agent architecture and the middleware technology such as CORBA (Common Object Request Broker Architecture). The system could integrate more resources and facilitate collaboration among agents to minimize misunderstanding between patients and doctors. A diagnosis method based on FMMNN (Fuzzy Min-Max Neural Network) was applied to the architecture to verify the advantages of the system.