期刊名称：The World of Computer Science and Information Technology Journal
印刷版ISSN：2221-0741
出版年度：2019
卷号：9, (2)
期号：2
页码：7-11
出版社：WCSIT Publishing
摘要：This research aims to use data mining to predict health care outcomes. We will investigate patterns of multiple chronic conditions (MCCs), or multimorbidity, among the US elderly population. The multimorbidity prediction model, as a general aspect, was not found in the literature, although some researchers have been exploring the risk of developing further chronic conditions after reporting an index disease. Data mining can provide richer results compared to those produced using a statistical approach and greater depth and breadth. It can also help professionals to identify the best time to intervene. In this research, the primary focus was on building disease knowledge using data mining algorithms for MCCs in the elderly. We identified potential morbidity groups using clustering and tested several prediction models on HCUP real data with high accuracy, where the highest accuracy of 99.05% was achieved by Logistic Regression.
关键词：Multimorbidity; Data mining; Classification; Clustering; Prediction; Chronic Diseases.
