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Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort

Globally, one of the biggest problems with the increase in the elderly population is dementia. However, dementia still has no fundamental cure. Therefore, it is important to predict and prevent dementia early. For early prediction of dementia, it is crucial to find dementia risk factors that increas...

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Detalles Bibliográficos
Autores principales: Choi, Jaekue, Kwon, Lee-Nam, Lim, Heuiseok, Chun, Hong-Woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579641/
https://www.ncbi.nlm.nih.gov/pubmed/33027971
http://dx.doi.org/10.3390/ijerph17197274
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author Choi, Jaekue
Kwon, Lee-Nam
Lim, Heuiseok
Chun, Hong-Woo
author_facet Choi, Jaekue
Kwon, Lee-Nam
Lim, Heuiseok
Chun, Hong-Woo
author_sort Choi, Jaekue
collection PubMed
description Globally, one of the biggest problems with the increase in the elderly population is dementia. However, dementia still has no fundamental cure. Therefore, it is important to predict and prevent dementia early. For early prediction of dementia, it is crucial to find dementia risk factors that increase a person’s risk of developing dementia. In this paper, the subject of dementia risk factor analysis and discovery studies were limited to gender, because it is assumed that the difference in the prevalence of dementia in men and women will lead to differences in the risk factors for dementia among men and women. This study analyzed the Korean National Health Information System—Senior Cohort using machine-learning techniques. By using the machine-learning technique, it was possible to reveal a very small causal relationship between data that are ignored using existing statistical techniques. By using the senior cohort, it was possible to analyze 6000 data that matched the experimental conditions out of 558,147 sample subjects over 14 years. In order to analyze the difference in dementia risk factors between men and women, three machine-learning-based dementia risk factor analysis models were constructed and compared. As a result of the experiment, it was found that the risk factors for dementia in men and women are different. In addition, not only did the results include most of the known dementia risk factors, previously unknown candidates for dementia risk factors were also identified. We hope that our research will be helpful in finding new dementia risk factors.
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spelling pubmed-75796412020-10-29 Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort Choi, Jaekue Kwon, Lee-Nam Lim, Heuiseok Chun, Hong-Woo Int J Environ Res Public Health Article Globally, one of the biggest problems with the increase in the elderly population is dementia. However, dementia still has no fundamental cure. Therefore, it is important to predict and prevent dementia early. For early prediction of dementia, it is crucial to find dementia risk factors that increase a person’s risk of developing dementia. In this paper, the subject of dementia risk factor analysis and discovery studies were limited to gender, because it is assumed that the difference in the prevalence of dementia in men and women will lead to differences in the risk factors for dementia among men and women. This study analyzed the Korean National Health Information System—Senior Cohort using machine-learning techniques. By using the machine-learning technique, it was possible to reveal a very small causal relationship between data that are ignored using existing statistical techniques. By using the senior cohort, it was possible to analyze 6000 data that matched the experimental conditions out of 558,147 sample subjects over 14 years. In order to analyze the difference in dementia risk factors between men and women, three machine-learning-based dementia risk factor analysis models were constructed and compared. As a result of the experiment, it was found that the risk factors for dementia in men and women are different. In addition, not only did the results include most of the known dementia risk factors, previously unknown candidates for dementia risk factors were also identified. We hope that our research will be helpful in finding new dementia risk factors. MDPI 2020-10-05 2020-10 /pmc/articles/PMC7579641/ /pubmed/33027971 http://dx.doi.org/10.3390/ijerph17197274 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Choi, Jaekue
Kwon, Lee-Nam
Lim, Heuiseok
Chun, Hong-Woo
Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort
title Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort
title_full Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort
title_fullStr Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort
title_full_unstemmed Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort
title_short Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort
title_sort gender-based analysis of risk factors for dementia using senior cohort
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579641/
https://www.ncbi.nlm.nih.gov/pubmed/33027971
http://dx.doi.org/10.3390/ijerph17197274
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