The Use of Data Mining Methods for the Prediction of Dementia: Evidence From the English Longitudinal Study of Aging

作     者：Yang, Hui Bath, Peter A. 

作者机构：Univ Sheffield Informat Sch Sheffield S1 4DP S Yorkshire England 

出 版 物：《IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS》 (IEEE J. Biomedical Health Informat.)

年 卷 期：2020年第24卷第2期

页      面：345-353页

核心收录：

学科分类：0710[理学-生物学] 0808[工学-电气工程] 1001[医学-基础医学(可授医学、理学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Mental health cognitive informatics gerontechnology 

摘      要：Dementia in older age is a major health concern with the increase in the aging population. Preventive measures to prevent or delay dementia symptoms are of utmost importance. In this study, a large and wide variety of factors from multiple domains were investigated using a large nationally representative sample of older people from the English Longitudinal Study of Ageing. Seven machine learning algorithms were implemented to build predictive models for performance comparison. A simple model ensemble approach was used to combine the prediction results of individual base models to further improve predictive power. A series of important factors in each domain area were identified. The findings from this study provide new evidence on factors that are associated with the dementia in later life. This information will help our understanding of potential risk factors for dementia and identify warning signs of the early stages of dementia. Longitudinal research is required to establish which factors may be causative and which factors may be a consequence of dementia.