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Heart disease is the leading cause of death in the world over the past 10 years. Researchers have been using several data mining techniques to help health care professionals in the diagnosis of heart disease. Decision Tree is one of the successful data mining techniques used. However, most research has applied J4.8 Decision Tree, based on Gain Ratio and(More)
—Heart disease is the leading cause of death in the world over the past 10 years. Researchers have been using several data mining techniques to help health care professionals in the diagnosis of heart disease patients. Decision Tree is one of the data mining techniques used in the diagnosis of heart disease showing considerable success. K-means clustering(More)
Heart disease is the leading cause of death in the world over the past 10 years. Researchers have been using several data mining techniques to help health care professionals in the diagnosis of heart disease. Naïve Bayes is one of the data mining techniques used in the diagnosis of heart disease showing considerable success. K-means clustering is one of the(More)
Despite the potential for information systems to improve societal conditions in developing countries, a lack of cumulative knowledge building to inform interventions hampers progress. This paper reports an integrated action research – design science project that addressed the problem of limited adoption of e-government in Bangladesh and contributes to(More)
This paper presents the first phase of a study on using current eLearning trends in course design to overcome challenges in eLearning within developing countries, particularly for non-tertiary training providers. The paper outlines the research and development of an ICT artefact using the Action Design Research method. The artefact will later be deployed(More)
In clinical medicine ,data mining deals with learning models to predict patient's health. The models can be dedicated to support clinicians in diagnostic and monitoring tasks. Data mining methods are commonly applied in clinical contexts to analyze retrospective data, thus giving healthcare professionals the opportunity to exploit enormous amounts of data(More)