Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , |
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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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 |
_version_ |
1800221785348636672 |