Can the Random Forests Model Improve the Power to Predict the Inten-tion of the Elderly in a Community to Participate in a Cognitive Health Promotion Program?
Background: We aimed to develop a model predicting the participation of the elderly in a cognitive health program using the random forest algorithm and presented baseline information for enhancing cognitive health. Methods: This study analyzed the raw data of Seoul Welfare Panel Study (SWPS) (20), w...
Saved in:
Main Author: | Haewon BYEON (Author) |
---|---|
Format: | Book |
Published: |
Tehran University of Medical Sciences,
2021-02-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Developing a nomogram for predicting depression in diabetic patients after COVID-19 using machine learning
by: Haewon Byeon, et al.
Published: (2023) -
Prediction of adolescent suicidal ideation after the COVID-19 pandemic: A nationwide survey of a representative sample of Korea
by: Haewon Byeon, et al.
Published: (2022) -
Predicting South Korean adolescents vulnerable to obesity after the COVID-19 pandemic using categorical boosting and shapley additive explanation values: A population-based cross-sectional survey
by: Haewon Byeon, et al.
Published: (2022) -
Combined Effects of tDCS and Language/Cognitive Intervention on the Naming of Dementia Patients: A Systematic Review and Meta-Analysis
by: Haewon BYEON
Published: (2020) -
Development of Keyword Trend Prediction Models for Obesity Before and After the COVID-19 Pandemic Using RNN and LSTM: Analyzing the News Big Data of South Korea
by: Gayeong Eom, et al.
Published: (2022)