A study of application of data mining algorithms in healthcare industry

Abstract

Data mining is a relatively new area of computer science that brings the concept of artificial intelligence, data structures, statistics, and database together. It is a high demand area because many organizations and businesses can benefit from it. There is no doubt that it is a great idea to use data mining tools in the healthcare systems to improve decisions made by the experts in this field. It has been seen that certain groups of people living in certain areas of the world with certain food diets carry certain diseases more than some other groups of people. It will be a great contribution to the healthcare system to know what the root of this type of problems is. The most critical challenge in this contribution is the issue of data management and utilization. Data mining algorithms can be used to find useful patterns in the patients' statistical data to find the associations among certain disease and possible causes of them. Thus, health care organizations are finding value as well as strategic applications to mining patient data, in general, and community data, in particular. While significant gains can be obtained and have been noted at the organizational level of analysis, much attention has been given to the individual, where the focal points have centered on privacy and security of patient data. While the privacy debate is a salient issue, data mining (DM) offers broader community-based gains that enable and improve healthcare forecasting, analyses, and visualization. This paper will study a few cases where data mining has been used to mine patient data to make decisions about patients and investigates how data mining can be beneficial in the context of healthcare system. ©American Society for Engineering education, 2013.