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

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Data

2014-11-01

Autores

Nascimento, L. F. C.
Rizol, Paloma Maria Silva Rocha [UNESP]
Peneluppi, A. P.

Título da Revista

ISSN da Revista

Título de Volume

Editor

Associação Brasileira de Divulgação Científica

Resumo

Exposure 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.

Descrição

Palavras-chave

Air pollutants, Fuzzy logic, Pneumonia, Particulate matter, Sulfur dioxide

Como citar

Brazilian Journal of Medical and Biological Research. Associação Brasileira de Divulgação Científica, v. 47, n. 11, p. 977-981, 2014.