Data Preprocessing and Apriori Algorithm Improvement in Medical Data Mining

Abstract

In recent years, various medical and health information systems have been widely used, and a large amount of medical-related data has been accumulated in the hospital. The rise of mobile medicine has made medical information more and more digitized, and the medical industry has entered a veritable era of big data. These medical data are extremely valuable for the diagnosis and treatment of diseases and medical research. Unfortunately, most hospitals currently only complete the collection and storage of patient medical data, but lack in-depth analysis and utilization of them. The method of data mining is used to discover the laws from the massive medical data, which provides a novel method for medical personnel to acquire knowledge. Among medical data mining methods, intelligent methods such as association rules, artificial neural networks, and rough set theory show unique advantages. Among them, association rule mining can analyze the frequency relationship of the data item set in the transaction set from a given set of data items and transaction sets.