An Uncertainty Reasoning Method for Abnormal ECG Detection

摘要：

The electrocardiogram(ECG) recognition is important for cardiovascular disease monitoring. It is significant to investigate automatic diagnosis methods related to wearable ECG instruments. This paper introduces Certainty Factor model based an uncertainty reasoning method for abnormal detection. It discusses the application and improvement of Certainty Factor model based on experts experience in electrocardiogram diagnosis and puts forward the thought of determining the model parameters by machine learning. The experiment results show that the improved Certainty Factor model has better accuracy. The stability of Certainty Factor model is better than that of Bayes when the number of the disease type is increased.

作者: WANG Li-ping SHEN Mi TONG Jia-fei DONG Jun

作者单位: Software Engineering Institute, East China Normal University, Shanghai, 200062, China

会议类型: 国际会议

会议名称: 2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)

会议地点: 济南

会议语种:英文

页码: 1091-1096

在线出版日期: 2009-08-14（万方平台首次上网日期，不代表论文的发表时间）