Modelling the impact of the disease on people with COPD – a comparison of feature selection methods

Detalhes bibliográficos
Autor(a) principal: Cabral, Jorge Vaz Ramos Rodrigues de
Data de Publicação: 2022
Outros Autores: Macedo, Pedro, Marques, Alda, Afreixo, Vera
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.34624/jshd.v4i1.29107
Resumo: Lockdown due to The COVID-19 pandemic is likely to have influenced the daily life of people with chronic obstructive pulmonary disease. Criteria to choose the most appropriate methods to select features in datasets are unclear. We aimed to compare feature selection methods and describe the effect of the COVID-19 lockdown, sociodemographic and clinical features on the impact of the disease on people with COPD. A total of 42 participants with mean age 66.3 years (sd 7.8), 3 to 4 comorbidities (64.3%) and a median CAT score of 9.0 ([Q1,Q3]=[5.3,11.0]) were included, 24 (57.1%) of whom in the pre-lockdown group. The model obtained with 3 features selected by the entropy approach was at least not worse than the remaining. Our model suggests that lockdown had no influence in COPD impact but those with comorbidities but no emergencies tended to recover well from the pandemic.
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spelling Modelling the impact of the disease on people with COPD – a comparison of feature selection methodsLockdown due to The COVID-19 pandemic is likely to have influenced the daily life of people with chronic obstructive pulmonary disease. Criteria to choose the most appropriate methods to select features in datasets are unclear. We aimed to compare feature selection methods and describe the effect of the COVID-19 lockdown, sociodemographic and clinical features on the impact of the disease on people with COPD. A total of 42 participants with mean age 66.3 years (sd 7.8), 3 to 4 comorbidities (64.3%) and a median CAT score of 9.0 ([Q1,Q3]=[5.3,11.0]) were included, 24 (57.1%) of whom in the pre-lockdown group. The model obtained with 3 features selected by the entropy approach was at least not worse than the remaining. Our model suggests that lockdown had no influence in COPD impact but those with comorbidities but no emergencies tended to recover well from the pandemic.University of Aveiro (UA) and Hospital Center of Baixo Vouga (CHBV)2022-07-20T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.34624/jshd.v4i1.29107oai:proa.ua.pt:article/29107Journal of Statistics on Health Decision; Vol 4 No 1 (2022): Special Issue - Statistics on Health Decision Making: Real World Data; 85-89Journal of Statistics on Health Decision; vol. 4 n.º 1 (2022): Special Issue - Statistics on Health Decision Making: Real World Data; 85-892184-5794reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttps://proa.ua.pt/index.php/jshd/article/view/29107https://doi.org/10.34624/jshd.v4i1.29107https://proa.ua.pt/index.php/jshd/article/view/29107/20665Copyright (c) 2022 Jorge Vaz Ramos Rodrigues de Cabral, Pedro Macedo, Alda Marques, Vera Afreixohttp://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessCabral, Jorge Vaz Ramos Rodrigues deMacedo, PedroMarques, AldaAfreixo, Vera2022-09-06T09:09:23Zoai:proa.ua.pt:article/29107Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:27:41.957420Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
title Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
spellingShingle Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
Cabral, Jorge Vaz Ramos Rodrigues de
title_short Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
title_full Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
title_fullStr Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
title_full_unstemmed Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
title_sort Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
author Cabral, Jorge Vaz Ramos Rodrigues de
author_facet Cabral, Jorge Vaz Ramos Rodrigues de
Macedo, Pedro
Marques, Alda
Afreixo, Vera
author_role author
author2 Macedo, Pedro
Marques, Alda
Afreixo, Vera
author2_role author
author
author
dc.contributor.author.fl_str_mv Cabral, Jorge Vaz Ramos Rodrigues de
Macedo, Pedro
Marques, Alda
Afreixo, Vera
description Lockdown due to The COVID-19 pandemic is likely to have influenced the daily life of people with chronic obstructive pulmonary disease. Criteria to choose the most appropriate methods to select features in datasets are unclear. We aimed to compare feature selection methods and describe the effect of the COVID-19 lockdown, sociodemographic and clinical features on the impact of the disease on people with COPD. A total of 42 participants with mean age 66.3 years (sd 7.8), 3 to 4 comorbidities (64.3%) and a median CAT score of 9.0 ([Q1,Q3]=[5.3,11.0]) were included, 24 (57.1%) of whom in the pre-lockdown group. The model obtained with 3 features selected by the entropy approach was at least not worse than the remaining. Our model suggests that lockdown had no influence in COPD impact but those with comorbidities but no emergencies tended to recover well from the pandemic.
publishDate 2022
dc.date.none.fl_str_mv 2022-07-20T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.34624/jshd.v4i1.29107
oai:proa.ua.pt:article/29107
url https://doi.org/10.34624/jshd.v4i1.29107
identifier_str_mv oai:proa.ua.pt:article/29107
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://proa.ua.pt/index.php/jshd/article/view/29107
https://doi.org/10.34624/jshd.v4i1.29107
https://proa.ua.pt/index.php/jshd/article/view/29107/20665
dc.rights.driver.fl_str_mv Copyright (c) 2022 Jorge Vaz Ramos Rodrigues de Cabral, Pedro Macedo, Alda Marques, Vera Afreixo
http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Jorge Vaz Ramos Rodrigues de Cabral, Pedro Macedo, Alda Marques, Vera Afreixo
http://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv University of Aveiro (UA) and Hospital Center of Baixo Vouga (CHBV)
publisher.none.fl_str_mv University of Aveiro (UA) and Hospital Center of Baixo Vouga (CHBV)
dc.source.none.fl_str_mv Journal of Statistics on Health Decision; Vol 4 No 1 (2022): Special Issue - Statistics on Health Decision Making: Real World Data; 85-89
Journal of Statistics on Health Decision; vol. 4 n.º 1 (2022): Special Issue - Statistics on Health Decision Making: Real World Data; 85-89
2184-5794
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institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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