Modelling the impact of the disease on people with COPD – a comparison of feature selection methods
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
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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oai:proa.ua.pt:article/29107 |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
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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 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
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 |
repository.mail.fl_str_mv |
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1799130142984896512 |