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Updated: Aug 18, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A predictive model for the risk of cognitive impairment in community middle-aged and older adults
Lining Pu1, Degong Pan1, Huihui Wang1
1Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, China.
Abstract:
Identifying individuals at high risk of cognitive impairment is essential for treatment and prevention strategies. We aimed to develop and validate a prediction model for evaluating the risk of cognitive impairment. Data were from the China Family Panel Studies (CFPS) and China Health and Retirement Longitudinal Study (CHARLS). A total of 14,265 subjects were selected for model development. The area under the curve(AUC) for the training, internal, and external validation sets were 0.775, 0.920, and 0.727, respectively. This model could be used to identify middle-aged and older adults aged 45 years and older at high risk of cognitive impairment.
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