Diwani, SalimMishol, SuzanKayange, Daniel S.Machuve, DinaSam, Anael2023-10-122023-10-122013Diwani, S., Mishol, S., Kayange, D. S., Machuve, D., & Sam, A. (2013). Overview applications of data mining in health care: The case study of Arusha region. International journal of computational engineering research, 3(8), 73-77.URL: https://tinyurl.com/366w867nhttp://hdl.handle.net/20.500.12661/4139Abstract. Full text article. Also available at https://tinyurl.com/366w867nData mining as one of many constituents of health care has been used intensively and extensively in many organizations around the globe as an efficient technique of finding correlations or patterns among dozens of fields in large relational databases to results into more useful health information. In healthcare, data mining is becoming increasingly popular and essential. Data mining applications can greatly benefits all parties involved in health care industry. The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform huge amount of data into useful information for decision making. This paper explores data mining applications in healthcare in Arusha region of Tanzania more particularly; it discusses data mining and its applications in major areas such as evaluation of treatment effectiveness, management of healthcare itself and lowering medical costs.enData miningHealthcare applicationKnowledge discoveryData warehousingData mining applicationsHealthcare managementData mining technologyhealthcareArticle