摘要
针对医学诊断知识获取问题,提出了基于Rough Sets理论的知识获取方法,利用该理论对数据进行分析,推理出可能规则,并提出了一种概率优化规则。通过实例分析,具体说明了该方法的实现步骤,包括连续信息系统的离散化、信息系统的约简、决策规则提取、决策模型生成等,讨论了知识处理的完整过程,能够有效地解决专家系统中知识获取的瓶颈问题。为人工智能技术在医学诊断领域的应用提供了新的思路。
Analyze how to extract medical diagnosis rules from medical cases. Based on the rough set theory, a way to acquiring knowledge was bring forward. Using this theory, the data was analyzed, possible rules was proposed, and a optimized probability formula was showed. By analyzing instances, the implement step of the way explained, including discreting continuous information system, reducting information system, acquiring decision rules and generating decision model, and so on. In the end, the whole process of knowledge acquisition was discussed, and this option can effective solve the choke point problem of acquiring knowledge in expert system. At the same time, it also provides new brainchild to solve the artificial intelligence technology's application in the field of medicinal diagnosing.
出处
《科技通报》
2005年第3期314-320,359,共8页
Bulletin of Science and Technology
基金
国家自然科学基金资助课题(60373062)
湖南省卫生厅科技基金资助项目(2001-Y89)
关键词
软件与算法
数据挖掘
ROUGHSET
医学诊断规则
连续信息系统
离散化
规则获取
software and arithmetic
data mine, rough sets, medicine diagnose rule, continuous information system, discretization, acquisition rules