Extracting Association Rules from Medical Health Records Using Multi-Criteria Decision Analysis

Abstract

Medical Health Records serves as rich knowledge sources for data mining. The availability of enormous amounts of medical data can be utilized to extract constructive facts using various data mining techniques. Numerous researches have been conducted in the field of medical data mining. In this paper, a novel approach is suggested to extract association rules from medical records by choosing the best association rule mining algorithm using multiple-criteria decision analysis. The purpose of the project is to discover correlation between diseases, diseases and symptoms, diseases and medicines.