Application Of Rough Set Theory And C-F Model In Automatic Recognition Of ECG

With the development of modern medicine and the advancement of technology, more and more intelligent information processing technologies are applied. Traditional methods based on confidence put many requirements on statistics and parameters. These defaults limited its application in Automatic Diagnoses System of Heart Disease(ADSHD) greatly. This paper combines the Uncertainty reasoning methods with attribute reduction of rough set theory according to the specific requirements of intelligent diagnoses system of heart disease. It is oriented to the foundamental research work and develops an expert system for ADSHD .Firstly, previous work on Automatic Diagnoses of Heart Disease is introduced and several main technologies and the foundamental principles of ADSHD are summed up. Secondly, rough set theory is introduced, then two new methods for attribute reduction are presented and compared with previous methods. We are the first to improve the C-F model adopting the attribute reduction of rough set theory. At last, an expert system for ADSHD is developed and the efficiency of the system is showed in practical application. And the rate of correct recognition get to what we want.