Estimating the average length of hospitalization due to pneumonia: a fuzzy approach

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorNascimento, L. F. C.-
Autor(es): dc.creatorRizol, Paloma Maria Silva Rocha-
Autor(es): dc.creatorPeneluppi, A. P.-
Data de aceite: dc.date.accessioned2021-03-10T21:23:52Z-
Data de disponibilização: dc.date.available2021-03-10T21:23:52Z-
Data de envio: dc.date.issued2015-02-02-
Data de envio: dc.date.issued2015-02-02-
Data de envio: dc.date.issued2014-11-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1590/1414-431X20143640-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/114159-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/114159-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionExposure to air pollutants is associated with hospitalizations due to pneumonia in children. We hypothesized the length of hospitalization due to pneumonia may be dependent on air pollutant concentrations. Therefore, we built a computational model using fuzzy logic tools to predict the mean time of hospitalization due to pneumonia in children living in São José dos Campos, SP, Brazil. The model was built with four inputs related to pollutant concentrations and effective temperature, and the output was related to the mean length of hospitalization. Each input had two membership functions and the output had four membership functions, generating 16 rules. The model was validated against real data, and a receiver operating characteristic (ROC) curve was constructed to evaluate model performance. The values predicted by the model were significantly correlated with real data. Sulfur dioxide and particulate matter significantly predicted the mean length of hospitalization in lags 0, 1, and 2. This model can contribute to the care provided to children with pneumonia.-
Formato: dc.format977-981-
Idioma: dc.languageen-
Publicador: dc.publisherAssociação Brasileira de Divulgação Científica-
Relação: dc.relationBrazilian Journal of Medical and Biological Research-
Relação: dc.relation1.492-
Direitos: dc.rightsopenAccess-
Palavras-chave: dc.subjectAir pollutants-
Palavras-chave: dc.subjectFuzzy logic-
Palavras-chave: dc.subjectPneumonia-
Palavras-chave: dc.subjectParticulate matter-
Palavras-chave: dc.subjectSulfur dioxide-
Título: dc.titleEstimating the average length of hospitalization due to pneumonia: a fuzzy approach-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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