【摘要】 针对目前智能医疗诊断领域的研究现状,为降低心肌梗塞疾病的误诊率,建立了专家系统与神经网络集成的用于医疗辅助诊断的智能决策支持系统.系统采用单参数动态搜索算法训练神经网络,效果明显优于传统的BP算法,极大地提高了神经网络的训练速度和分类精度.临床应用的结果表明,系统的诊断敏感性、特异性、准确性明显高于临床医生,对提高急性心肌梗塞的正确诊断率具有重要研究价值.更多还原

【Abstract】 The thesis firstly analyzes the actuality of intelligent medical diagnostic field.To reduce the mis-diagnosis ratio,an intelligent decision support system for the diagnosis of acute myocardial infarction is built.For the single parameter dynamic searching method is used to train neural network,which proves to work well than BP algorithm,the training speed and classifying precision of neural network are increased.Tested by the diagnostic cases in clinical,the sensitivity,specificity and accuracy of the diagnosis system are higher than those of the physicians.It is significant to improve the accuracy to diagnose acute myocardial infarction.更多还原