A Medical Expert System to Identify Major Factor of Diseases Using P-Rules

Nowadays, people face various health related problems due to the busy Iifestyle and hectic work pressure. Under this circumstance, if it is possible to have a system that identifies the major causes of health related problems then people can follow some precautionary measures to prevent those causes and can have disease free life. This paper proposes an algorithm, called Rule Based Major Feature Identification (RBMFI) which identifies major feature of medical problems by pruning p-rules generated by decision tree. RBMFI algorithm comprises of three phases: Rule generation, Rule pruning and Attribute pruning. Rule generation generates the rules using decision tree, rule pruning removes the rules that do not affect the overall classification accuracy and attribute pruning keeps only the major feature of a decision. Finally, the major feature is treated as major cause of a decision (disease). The proposed method is validated with three medical datasets taken from UCI repository. It is observed from the experimental results that the proposed RBMFI can identify the major feature with good accuracy.