Research And Implementation Of Intelligent Mechanism For Clinical Decision Support

Based on medical knowledge of clinical pathways, clinical guidelines and expert consensus, etc., Clinical Decision Support Systems(CDSS) can effectively assist the clinicians in disease diagnosis and treatment. In order to provide standardized clinical training to junior doctors and local hospital doctors, based on the intelligent decision support capabilities of CDSS, to research and develop CDSS training version, simulating realistic clinical scenarios in the training version, will be of great significance.This paper proposes a rule-based intelligent clinical decision support mechanism. By means of rule inference, the system can monitor the clinical behaviors in the virtual diagnosis and treatment process and guide the trainers to carry out standardized clinical behaviors and processes. Firstly, the paper will give the analysis of the needs of CDSS training version, in order to clarify the application background of intelligent decision support. And then the runtime procedures of decision support systems will be modeled and designed and the software architecture of the CDSS training version will be given to define the interaction methods and interactive data of the intelligent clinical decision support mechanism. Secondly, the rule XML-based language will be designed and given based on the medical knowledge of clinical pathways, clinical guidelines and expert consensus, etc. The clinical rules would be represented as computer recognizable rules definition. After that, the relevant data will be analyzed in order to provide data to support the rule inference, and particularly, a medical case modeling will be proposed. Finally, based on the research and design above, around the parsing and execution of rules, and the state control of rule inference, this paper will design and implement the rules engine. The detailed analysis and discusses will be given to design and implement the rules engine framework and its functional modules.Based on CDSS training version- coronary heart disease, several typical test cases will be given to test and verify the rules engine design and implementation, and the performance will also be tested and analyzed. The results show that the design and implementation of the rule-based intelligent decision-making mechanisms meets this paper's goals.