Objective: Improvements in hospital devices, storage, and networks have led to an explosive growth in medical information. The traditional information management is challenged by satisfying people's need of clinical service due to the diversity of information sources. Methods: In this paper, we present an approach to medical knowledge representation and mining based on Natural Language Processing methods. Result & Conclusion: It is helpful for users to gain useful insight from the massive data by combining automated analysis techniques with interactive visualizations. Experiments show that visual analytics facilitate users to deal with information overloads and aid medical diagnosis decision.%目的:海量医学信息的快速增长以及信息来源的多样性与无序性,使得传统的医学信息的组织方式很难满足人们对信息服务的需求.方法:采用自然语言处理技术多通道挖掘医疗知识,给出一种基于"规则架+规则体"的医疗知识表示与处理方法.结果及结论:通过结合交互式和自动分析技术,可以有效帮助人们从海量数据中获取到有用的信息模式,减轻人们对数据进行分析的负担,可在诊疗服务中有效辅助医学决策活动.
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