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Article history: Received: 30 April, 2019 Accepted: 07 September, 2019 Online: 08 October, 2019 Data mining is recognized as an effective technique for extracting and retrieving valuable information or decision from the vast available data. Because of the nature of the functionality of medical centers and hospitals, their data centers contain a collection of valuable information about their patients. By properly processing these data, different applications can be developed to utilize them. These applications could participate in predicting and diagnosing particular diseases. Two prime diseases realized to impact the overall health of society are heart diseases and diabetes. The presented work intends to develop and test a software application that helps doctors and practitioners predict the emergence of noncommunicable diseases (NCDs) such as diabetes and heart diseases. The application applies the predictive data mining model to the medical records which are collected from the Bahrain Defense Force Hospital (BDFH). The BDFH doctors evaluated the application and executed it on actual patients. The results obtained are accurately matching the expectation of doctors in BDFH. All kinds of risks are categorized appropriately according to the defined categories. As a conclusion, this application can help doctors in making proper decisions toward patient health risks. In addition, data mining is more supportive for the health sector and is essential for exploring the knowledge to be used in the health care sector.

Prediction of Non-Communicable Diseases Using Class Comparison Data Mining