Method for Knowledge Acquisition and Decision-Making Process Analysis in Clinical Decision Support System

摘要

The traditional clinical decision support system (CDSS) is based on the rule engine and knowledge base which are arranged and imported into the system by the relevant personnel before the system running. Therefore once the system is put into use, the knowledge and rules will be rarely revised and updated dynamically according to the actual clinical environment. In addition, conventional systems has failed to take full advantage of the data stored in Hospital Information System (HIS) to excavate implicit knowledge of the diagnosis and treatment. Furthermore, the lack of logging mechanism during the diagnosis and treatment decisions link results in the imperfection of the learning ability for the CDSS. To solve the above problems above, this paper proposes to introduce the knowledge mining technology into the CDSS to use the data in the HIS for knowledge mining activities. And the use of the excavated knowledge and rules makes the knowledge systems dynamically updated and expanded. With using the clinical log to store the information of the decision-making process, it will be easy to study, analysis, assessment the implicit knowledge in order to find the problems and make targeted to improve them to achieve the purpose of improve the decision-making accuracy.