Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Ciência & Saúde Coletiva (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232019000301083 |
Resumo: | Abstract Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory diseases. We constructed a fuzzy model for prediction of hospitalizations due to pneumonia, bronchitis, bronchiolitis and asthma second exposure to fine particulate matter (PM2.5) in residents of Volta Redonda, RJ, in 2012. The model contains two inputs, PM2.5 and temperature, with three membership functions for each input, and an output with three membership functions for admissions, which were obtained from DATASUS. There were 752 hospitalizations in the period, the average concentration of PM2.5 was 17.1 µg/m3 (SD = 4.4). The model showed a good accuracy with PM2.5, the result was between 90% and 76.5% for lags 1, 2 and 3, a sensitivity of up to 95%. This study provides support for creating executable software with a low investment, along with the use of a portable instrument could allow number of hospital admission due to respiratory diseases and provide support to local health managers. Furthermore, the fuzzy model is very simple and involves low computational costs, an implementation making possible. |
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Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical modelAir pollutionParticulate matterRespiratory diseasesfuzzy logicMathematical modelingAbstract Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory diseases. We constructed a fuzzy model for prediction of hospitalizations due to pneumonia, bronchitis, bronchiolitis and asthma second exposure to fine particulate matter (PM2.5) in residents of Volta Redonda, RJ, in 2012. The model contains two inputs, PM2.5 and temperature, with three membership functions for each input, and an output with three membership functions for admissions, which were obtained from DATASUS. There were 752 hospitalizations in the period, the average concentration of PM2.5 was 17.1 µg/m3 (SD = 4.4). The model showed a good accuracy with PM2.5, the result was between 90% and 76.5% for lags 1, 2 and 3, a sensitivity of up to 95%. This study provides support for creating executable software with a low investment, along with the use of a portable instrument could allow number of hospital admission due to respiratory diseases and provide support to local health managers. Furthermore, the fuzzy model is very simple and involves low computational costs, an implementation making possible.ABRASCO - Associação Brasileira de Saúde Coletiva2019-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232019000301083Ciência & Saúde Coletiva v.24 n.3 2019reponame:Ciência & Saúde Coletiva (Online)instname:Associação Brasileira de Saúde Coletiva (ABRASCO)instacron:ABRASCO10.1590/1413-81232018243.08172017info:eu-repo/semantics/openAccessVieira,Luciana Cristina Pompeo Ferreira da SilvaRizol,Paloma Maria da Silva RochaNascimento,Luiz Fernando Costaeng2019-07-15T00:00:00Zoai:scielo:S1413-81232019000301083Revistahttp://www.cienciaesaudecoletiva.com.brhttps://old.scielo.br/oai/scielo-oai.php||cienciasaudecoletiva@fiocruz.br1678-45611413-8123opendoar:2019-07-15T00:00Ciência & Saúde Coletiva (Online) - Associação Brasileira de Saúde Coletiva (ABRASCO)false |
dc.title.none.fl_str_mv |
Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model |
title |
Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model |
spellingShingle |
Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model Vieira,Luciana Cristina Pompeo Ferreira da Silva Air pollution Particulate matter Respiratory diseases fuzzy logic Mathematical modeling |
title_short |
Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model |
title_full |
Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model |
title_fullStr |
Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model |
title_full_unstemmed |
Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model |
title_sort |
Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model |
author |
Vieira,Luciana Cristina Pompeo Ferreira da Silva |
author_facet |
Vieira,Luciana Cristina Pompeo Ferreira da Silva Rizol,Paloma Maria da Silva Rocha Nascimento,Luiz Fernando Costa |
author_role |
author |
author2 |
Rizol,Paloma Maria da Silva Rocha Nascimento,Luiz Fernando Costa |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Vieira,Luciana Cristina Pompeo Ferreira da Silva Rizol,Paloma Maria da Silva Rocha Nascimento,Luiz Fernando Costa |
dc.subject.por.fl_str_mv |
Air pollution Particulate matter Respiratory diseases fuzzy logic Mathematical modeling |
topic |
Air pollution Particulate matter Respiratory diseases fuzzy logic Mathematical modeling |
description |
Abstract Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory diseases. We constructed a fuzzy model for prediction of hospitalizations due to pneumonia, bronchitis, bronchiolitis and asthma second exposure to fine particulate matter (PM2.5) in residents of Volta Redonda, RJ, in 2012. The model contains two inputs, PM2.5 and temperature, with three membership functions for each input, and an output with three membership functions for admissions, which were obtained from DATASUS. There were 752 hospitalizations in the period, the average concentration of PM2.5 was 17.1 µg/m3 (SD = 4.4). The model showed a good accuracy with PM2.5, the result was between 90% and 76.5% for lags 1, 2 and 3, a sensitivity of up to 95%. This study provides support for creating executable software with a low investment, along with the use of a portable instrument could allow number of hospital admission due to respiratory diseases and provide support to local health managers. Furthermore, the fuzzy model is very simple and involves low computational costs, an implementation making possible. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-03-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232019000301083 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232019000301083 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1413-81232018243.08172017 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
ABRASCO - Associação Brasileira de Saúde Coletiva |
publisher.none.fl_str_mv |
ABRASCO - Associação Brasileira de Saúde Coletiva |
dc.source.none.fl_str_mv |
Ciência & Saúde Coletiva v.24 n.3 2019 reponame:Ciência & Saúde Coletiva (Online) instname:Associação Brasileira de Saúde Coletiva (ABRASCO) instacron:ABRASCO |
instname_str |
Associação Brasileira de Saúde Coletiva (ABRASCO) |
instacron_str |
ABRASCO |
institution |
ABRASCO |
reponame_str |
Ciência & Saúde Coletiva (Online) |
collection |
Ciência & Saúde Coletiva (Online) |
repository.name.fl_str_mv |
Ciência & Saúde Coletiva (Online) - Associação Brasileira de Saúde Coletiva (ABRASCO) |
repository.mail.fl_str_mv |
||cienciasaudecoletiva@fiocruz.br |
_version_ |
1754213043459325952 |