【摘要】 本项研究是在建立急性心肌梗塞(AMI)病历数据库基础上统计分析、参考文献资料,吸收专家经验,提炼与AMI急性期预后较为密切的指标。而后用模糊集方法提出了危机度的概念,确定了各指标组间的关系及其权值。同时结合总结AMI临床诊治的过程和经验,以人工智能技术为指导,采用定性和定量相结合、模糊集与数理逻辑相结合的方法,构造出了一个以发病五天以内临床资料预估急性期(8)病情的专家系统。符合率及验证符合率均达90％以上。文中讨论了本项研究的方法、特点和实用价值。该系统不但可以早期及时预估AMI病情的严重程度,还可以帮助医生寻找影响预后的主要因素,施以恰当的治疗措施。更多还原

【Abstract】 <ABSTRACT>This paper reported establishment of expert system for acute stageprognosis of acute myocardial infarction based on establishing AMI database, making statistic analysis, acceotubg expert exoeruebces, refiningindexes intimately relateed to acute stage of AMI. By using fuzzy pro-bability method, we advanced a concept of endangerment degree andstudied the relationship between the indexes and prognosis. Meanwhileguided by artificial intelligence, we summarized the AMI clinical coruseand experience of diagnosis and cure. Using in combination of qualitat-ive and quantitative data, as well as fuzzy set and mathematical logiomethods, we built an expert system for estimation of state of patient inacute stage of AMI from clinical data within five days of disease andfor finding out main factors influencing prognosis so as to provide pro-per treatment. The correct rate of diagnosis was more than 90% usingthe expert system. Characteristics and practical vaue of the methodwere also discussed.更多还原