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ID 118876
Author
Nakao, Hidetoshi Josai International University
Imaoka, Masakazu Osaka Kawasaki Rehabilitation University
Hida, Mitsumasa Osaka Kawasaki Rehabilitation University
Imai, Ryota Osaka Kawasaki Rehabilitation University
Nakamura, Misa Osaka Kawasaki Rehabilitation University
Keywords
Feature selection
Hallux Valgus
Manchester Scale
SVM-RFE
Content Type
Journal Article
Description
Introduction
This cross-sectional study aimed to determine the factors related to hallux valgus (HV) and their importance using support vector machine-recursive feature elimination (SVM-RFE).
Methods
A total of 864 participants aged ≥ 18 years were enrolled. The Manchester scale was used to determine the presence of HV (summed scores for both feet ≥ 4). The questionnaire included items such as age, sex, height, weight, and foot measurements. These internal factors were analyzed to determine if they are related to HV using SVM-RFE.
Results
The results of tenfold cross-validation using SVM-RFE revealed that the numbers of feature selections were 10, 10, and 9 for age, sex, and body weight, respectively, and these factors were shown to be related to HV. HV was found to be more common in women than in men (women, 24.9%; men, 7.6%), but the sex difference was not significant in older people.
Conclusion
Age and sex were found to be important factors associated with HV identified via feature selection using SVM-RFE.
Journal Title
BMC Musculoskeletal Disorders
ISSN
14712474
NCID
AA12035278
Publisher
Springer Nature|BioMed Central
Volume
24
Start Page
534
Published Date
2023-06-29
Rights
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
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language
eng
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departments
Science and Technology