A medical support treatment model based on data mining

Abstract

Chronic hepatitis B is a stubborn disease afflicting mankind. Interferon alpha treatment is one of available antiviral options of treating chronic hepatitis B at present. However, the expensive treatment costs and side effects greatly hindered its application. It is useful in practice to patients suffering from hepatitis B that giving the analysis before treatment and predicting the possible effect of treatment according to the physiological mechanism and pathological condition of the patients themselves. This research focus on setting a hepatitis B auxiliary treatment model based on data mining technique which exploits the relationship between the treatment results and the characteristic of different patients. The experiment results on real data sets show that our method is effective and practicable.