Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study

Detalhes bibliográficos
Autor(a) principal: Sousa, Clóvis Arlindo de
Data de Publicação: 2006
Outros Autores: Duarte, Paulo Schiavom, Pereira, Júlio Cesar Rodrigues
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista de Saúde Pública
Texto Completo: https://www.revistas.usp.br/rsp/article/view/32150
Resumo: OBJECTIVE: To develop and compare two mathematical models, the first one based on logistic regression and the second one on fuzzy sets theory, aiming at defining a laboratory testing-based measure of indication for submitting patients to parathyroid scintigraphy. METHODS: One-hundred and ninety-four patients with serum calcium and parathyroid hormone available were identified from the data registry of parathyroid scintigraphy of a diagnostic laboratory in São Paulo, Southern Brazil, in the period between January 2000 and December 2004. The logistic regression model was developed using SPSS and the fuzzy model was developed using MatLab software programs. The performances of both models were compared using ROC curves. RESULTS: The performance of both models were statistically different (p=0.026). The area under the ROC curves were 0.862 (95% CI: 0.811-0.913) for the logistic regression model and 0.887 (95% CI: 0.840-0.933) for the fuzzy model. The latter had the advantage of allowing to making decisions based on parathyroid hormone information within a non-discriminating range of calcium values. CONCLUSIONS: The mathematical model based on fuzzy sets theory seemed to be more useful than the logistic model in the decision making for scintigraphy indication. However, inferences can be made only regarding model comparison and not for parathyroid scintigraphy itself since the data analyzed was not representative of any population.
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spelling Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study Lógica fuzzy e regressão logística na decisão para prática de cintilografia das paratiróides Modelos matemáticosLógica fuzzyModelos logísticosTécnicas de apoio para decisãoGlândulas paratireóides^i1^scintilograCálcio^i1^suso diagnóstHormônio paratireóideo^i1^suso diagnóstMathematical modelsFuzzy logicLogistic modelsDecision support techniquesParathyroid glands^i2^sradionuclide imagCalcium^i2^sdiagnosticParathyroid hormone^i2^sdiagnostic OBJECTIVE: To develop and compare two mathematical models, the first one based on logistic regression and the second one on fuzzy sets theory, aiming at defining a laboratory testing-based measure of indication for submitting patients to parathyroid scintigraphy. METHODS: One-hundred and ninety-four patients with serum calcium and parathyroid hormone available were identified from the data registry of parathyroid scintigraphy of a diagnostic laboratory in São Paulo, Southern Brazil, in the period between January 2000 and December 2004. The logistic regression model was developed using SPSS and the fuzzy model was developed using MatLab software programs. The performances of both models were compared using ROC curves. RESULTS: The performance of both models were statistically different (p=0.026). The area under the ROC curves were 0.862 (95% CI: 0.811-0.913) for the logistic regression model and 0.887 (95% CI: 0.840-0.933) for the fuzzy model. The latter had the advantage of allowing to making decisions based on parathyroid hormone information within a non-discriminating range of calcium values. CONCLUSIONS: The mathematical model based on fuzzy sets theory seemed to be more useful than the logistic model in the decision making for scintigraphy indication. However, inferences can be made only regarding model comparison and not for parathyroid scintigraphy itself since the data analyzed was not representative of any population. OBJETIVO: Desenvolver e comparar dois modelos matemáticos, um deles baseado em regressão logística e o outro em teoria de conjuntos fuzzy, para definir a indicação para a realização do exame cintilográfico a partir de resultados dos exames laboratoriais. MÉTODOS: Foram identificados 194 pacientes que tiveram cálcio e paratormônio séricos medidos a partir da base de registros de cintilografia de paratiróides realizadas em laboratório de diagnóstico de São Paulo, no período de janeiro de 2000 a dezembro de 2004. O modelo de regressão logística foi desenvolvido utilizando-se o software SPSS e o modelo fuzzy, o Matlab. A performance dos modelos foi comparada utilizando-se curvas ROC. RESULTADOS: Os modelos apresentaram diferenças estatisticamente significantes (p=0,026) nos seus desempenhos. A área sob a curva ROC do modelo de regressão logística foi de 0,862 (IC 95%: 0,811-0,913) e do modelo de lógica fuzzy foi 0,887 (IC 95%: 0,840-0,933). Este último destacou-se como particularmente útil porque, ao contrário do modelo logístico, mostrou capacidade de utilizar informações de paratormônio em intervalo em que os valores de cálcio mostraram-se pouco discriminantes. CONCLUSÕES: O modelo matemático baseado em teoria de conjuntos fuzzy pareceu ser mais adequado do que o baseado em regressão logística como método para decisão da realização de cintilografia das paratiróides. Todavia, sendo resultado de um exercício metodológico, inferências sobre o comportamento do objeto podem ser impróprias, dada a não representatividade populacional dos dados. Universidade de São Paulo. Faculdade de Saúde Pública2006-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/rsp/article/view/3215010.1590/S0034-89102006000600021Revista de Saúde Pública; Vol. 40 No. 5 (2006); 898-906 Revista de Saúde Pública; Vol. 40 Núm. 5 (2006); 898-906 Revista de Saúde Pública; v. 40 n. 5 (2006); 898-906 1518-87870034-8910reponame:Revista de Saúde Públicainstname:Universidade de São Paulo (USP)instacron:USPporhttps://www.revistas.usp.br/rsp/article/view/32150/34237Copyright (c) 2017 Revista de Saúde Públicainfo:eu-repo/semantics/openAccessSousa, Clóvis Arlindo deDuarte, Paulo SchiavomPereira, Júlio Cesar Rodrigues2012-07-08T23:15:16Zoai:revistas.usp.br:article/32150Revistahttps://www.revistas.usp.br/rsp/indexONGhttps://www.revistas.usp.br/rsp/oairevsp@org.usp.br||revsp1@usp.br1518-87870034-8910opendoar:2012-07-08T23:15:16Revista de Saúde Pública - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
Lógica fuzzy e regressão logística na decisão para prática de cintilografia das paratiróides
title Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
spellingShingle Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
Sousa, Clóvis Arlindo de
Modelos matemáticos
Lógica fuzzy
Modelos logísticos
Técnicas de apoio para decisão
Glândulas paratireóides^i1^scintilogra
Cálcio^i1^suso diagnóst
Hormônio paratireóideo^i1^suso diagnóst
Mathematical models
Fuzzy logic
Logistic models
Decision support techniques
Parathyroid glands^i2^sradionuclide imag
Calcium^i2^sdiagnostic
Parathyroid hormone^i2^sdiagnostic
title_short Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
title_full Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
title_fullStr Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
title_full_unstemmed Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
title_sort Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
author Sousa, Clóvis Arlindo de
author_facet Sousa, Clóvis Arlindo de
Duarte, Paulo Schiavom
Pereira, Júlio Cesar Rodrigues
author_role author
author2 Duarte, Paulo Schiavom
Pereira, Júlio Cesar Rodrigues
author2_role author
author
dc.contributor.author.fl_str_mv Sousa, Clóvis Arlindo de
Duarte, Paulo Schiavom
Pereira, Júlio Cesar Rodrigues
dc.subject.por.fl_str_mv Modelos matemáticos
Lógica fuzzy
Modelos logísticos
Técnicas de apoio para decisão
Glândulas paratireóides^i1^scintilogra
Cálcio^i1^suso diagnóst
Hormônio paratireóideo^i1^suso diagnóst
Mathematical models
Fuzzy logic
Logistic models
Decision support techniques
Parathyroid glands^i2^sradionuclide imag
Calcium^i2^sdiagnostic
Parathyroid hormone^i2^sdiagnostic
topic Modelos matemáticos
Lógica fuzzy
Modelos logísticos
Técnicas de apoio para decisão
Glândulas paratireóides^i1^scintilogra
Cálcio^i1^suso diagnóst
Hormônio paratireóideo^i1^suso diagnóst
Mathematical models
Fuzzy logic
Logistic models
Decision support techniques
Parathyroid glands^i2^sradionuclide imag
Calcium^i2^sdiagnostic
Parathyroid hormone^i2^sdiagnostic
description OBJECTIVE: To develop and compare two mathematical models, the first one based on logistic regression and the second one on fuzzy sets theory, aiming at defining a laboratory testing-based measure of indication for submitting patients to parathyroid scintigraphy. METHODS: One-hundred and ninety-four patients with serum calcium and parathyroid hormone available were identified from the data registry of parathyroid scintigraphy of a diagnostic laboratory in São Paulo, Southern Brazil, in the period between January 2000 and December 2004. The logistic regression model was developed using SPSS and the fuzzy model was developed using MatLab software programs. The performances of both models were compared using ROC curves. RESULTS: The performance of both models were statistically different (p=0.026). The area under the ROC curves were 0.862 (95% CI: 0.811-0.913) for the logistic regression model and 0.887 (95% CI: 0.840-0.933) for the fuzzy model. The latter had the advantage of allowing to making decisions based on parathyroid hormone information within a non-discriminating range of calcium values. CONCLUSIONS: The mathematical model based on fuzzy sets theory seemed to be more useful than the logistic model in the decision making for scintigraphy indication. However, inferences can be made only regarding model comparison and not for parathyroid scintigraphy itself since the data analyzed was not representative of any population.
publishDate 2006
dc.date.none.fl_str_mv 2006-10-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/rsp/article/view/32150
10.1590/S0034-89102006000600021
url https://www.revistas.usp.br/rsp/article/view/32150
identifier_str_mv 10.1590/S0034-89102006000600021
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://www.revistas.usp.br/rsp/article/view/32150/34237
dc.rights.driver.fl_str_mv Copyright (c) 2017 Revista de Saúde Pública
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Revista de Saúde Pública
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Faculdade de Saúde Pública
publisher.none.fl_str_mv Universidade de São Paulo. Faculdade de Saúde Pública
dc.source.none.fl_str_mv Revista de Saúde Pública; Vol. 40 No. 5 (2006); 898-906
Revista de Saúde Pública; Vol. 40 Núm. 5 (2006); 898-906
Revista de Saúde Pública; v. 40 n. 5 (2006); 898-906
1518-8787
0034-8910
reponame:Revista de Saúde Pública
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Revista de Saúde Pública
collection Revista de Saúde Pública
repository.name.fl_str_mv Revista de Saúde Pública - Universidade de São Paulo (USP)
repository.mail.fl_str_mv revsp@org.usp.br||revsp1@usp.br
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