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Interrelationship between the general characteristics of Korean stroke patients and the variables of the sexual functions: random forest and boosting algorithm
[Purpose] The purpose of this study is to examine patient preferences for counseling related to sexuality post-stroke in Korea. [Subjects and Methods] A survey was conducted on 200 stroke patients. Among the 200 submitted questionnaires, 156 responded but 147 cases are available. The questionnaire i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Society of Physical Therapy Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5430258/ https://www.ncbi.nlm.nih.gov/pubmed/28533595 http://dx.doi.org/10.1589/jpts.29.613 |
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author | Yoon, Jung-Gyu Zarayeneh, Neda Suh, Sang C. |
author_facet | Yoon, Jung-Gyu Zarayeneh, Neda Suh, Sang C. |
author_sort | Yoon, Jung-Gyu |
collection | PubMed |
description | [Purpose] The purpose of this study is to examine patient preferences for counseling related to sexuality post-stroke in Korea. [Subjects and Methods] A survey was conducted on 200 stroke patients. Among the 200 submitted questionnaires, 156 responded but 147 cases are available. The questionnaire is composed of 27 questions such as 8 independent variables related to the general characteristics of the patients, 7 dependent variables in conjunction with sexual intercourse and changed muscle tone, 6 questions regarding to changed sexual function, and 6 questions about a changed motor and a sensory function after stroke. To analyze the factors related to a sexual function after a stroke, we used the random forest, boosting algorithm and MANOVA. [Results] The most important variable in variable group 1 is VAR1, and then VAR22, VAR23, VAR26, VAR27, VAR25, VAR21 and VAR 24 respectively. The most important variable in variable group 2 is VAR22, and then VAR26, VAR23, VAR25, VAR1, VAR27, VAR21 and VAR 24. Finally, for variable group 3, VAR1 has the most important percentage, and we have the order as VAR26, VAR23, VAR27, VAR22, VAR25, VAR21 and VAR 24 among the rest of variables. The result of variable importance in boosting algorithm is somehow the same as that of random forest. [Conclusion] As a result of our analysis, we figured out that duration of illness, age, and education level are important factors of sexual functions for Korean Stroke patients. |
format | Online Article Text |
id | pubmed-5430258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Society of Physical Therapy Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54302582017-05-22 Interrelationship between the general characteristics of Korean stroke patients and the variables of the sexual functions: random forest and boosting algorithm Yoon, Jung-Gyu Zarayeneh, Neda Suh, Sang C. J Phys Ther Sci Original Article [Purpose] The purpose of this study is to examine patient preferences for counseling related to sexuality post-stroke in Korea. [Subjects and Methods] A survey was conducted on 200 stroke patients. Among the 200 submitted questionnaires, 156 responded but 147 cases are available. The questionnaire is composed of 27 questions such as 8 independent variables related to the general characteristics of the patients, 7 dependent variables in conjunction with sexual intercourse and changed muscle tone, 6 questions regarding to changed sexual function, and 6 questions about a changed motor and a sensory function after stroke. To analyze the factors related to a sexual function after a stroke, we used the random forest, boosting algorithm and MANOVA. [Results] The most important variable in variable group 1 is VAR1, and then VAR22, VAR23, VAR26, VAR27, VAR25, VAR21 and VAR 24 respectively. The most important variable in variable group 2 is VAR22, and then VAR26, VAR23, VAR25, VAR1, VAR27, VAR21 and VAR 24. Finally, for variable group 3, VAR1 has the most important percentage, and we have the order as VAR26, VAR23, VAR27, VAR22, VAR25, VAR21 and VAR 24 among the rest of variables. The result of variable importance in boosting algorithm is somehow the same as that of random forest. [Conclusion] As a result of our analysis, we figured out that duration of illness, age, and education level are important factors of sexual functions for Korean Stroke patients. The Society of Physical Therapy Science 2017-04-20 2017-04 /pmc/articles/PMC5430258/ /pubmed/28533595 http://dx.doi.org/10.1589/jpts.29.613 Text en 2017©by the Society of Physical Therapy Science. Published by IPEC Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (by-nc-nd) License. (CC-BY-NC-ND 4.0: https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Article Yoon, Jung-Gyu Zarayeneh, Neda Suh, Sang C. Interrelationship between the general characteristics of Korean stroke patients and the variables of the sexual functions: random forest and boosting algorithm |
title | Interrelationship between the general characteristics of Korean stroke
patients and the variables of the sexual functions: random forest and boosting
algorithm |
title_full | Interrelationship between the general characteristics of Korean stroke
patients and the variables of the sexual functions: random forest and boosting
algorithm |
title_fullStr | Interrelationship between the general characteristics of Korean stroke
patients and the variables of the sexual functions: random forest and boosting
algorithm |
title_full_unstemmed | Interrelationship between the general characteristics of Korean stroke
patients and the variables of the sexual functions: random forest and boosting
algorithm |
title_short | Interrelationship between the general characteristics of Korean stroke
patients and the variables of the sexual functions: random forest and boosting
algorithm |
title_sort | interrelationship between the general characteristics of korean stroke
patients and the variables of the sexual functions: random forest and boosting
algorithm |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5430258/ https://www.ncbi.nlm.nih.gov/pubmed/28533595 http://dx.doi.org/10.1589/jpts.29.613 |
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