|
KMID : 1155220220470040339
|
|
Journal of the Korean Society of Health Information and Health Statistics
2022 Volume.47 No. 4 p.339 ~ p.348
|
|
|
Prediction of Depression in Older Adults Using Wide & Deep Learning Model
|
|
Lim June-Huyck
Lim Dar-Oh
|
|
|
Abstract
|
|
|
Objectives: This study aims to suggest a depression prediction model using variables indirectly related to depression, which helps determine whether the target is depressed.
Methods: This study using Korea Institute for Health and Social Affairs (KIHSA)’s 2011, 2014, 2017 National Survey of Older Kore- ans, and the total number of subjects of the study is 30,571 elderly people 65 years of age or older.
Results: The analysis way is deep learning especially Wide & Deep Learning model that separately learns simple data and complex data. The dependent variable is depression, and the independent variable is a total of 30 variables related to personal attributes, economic status, human relationships, health status, health behavior, and life satisfaction. As a result of the main study, all the independent variables used were found to be correlated with depression, performance of Wide & Deep model is 77.9% accuracy, 65.7% recall, 73.8% precision, 85.5% specificity, 69.5% F1-score, 85.3% AUROC, 90.0% AUPRC.
Conclusions: It is expected that it will be helpful for the welfare of the elderly by searching for depressed patients at a lower cost and searching for potential depressed patients who want to hide their depression.
|
|
|
KEYWORD
|
|
|
Deep learning, Depression, Older, National Survey of Older Koreans
|
|
|
FullTexts / Linksout information
|
|
|
|
|
|
Listed journal information
|
|
|
|