Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/37638 |
Resumo: | Myocardial revascularization surgery is one of the recommended approaches for the treatment of chronic coronary disease. Several complications related to mortality, sequelae, length of stay, and hospital costs are also associated with this procedure. Death rates and complications depend on the characteristics of each patient. Knowing the factors related to hospital mortality and complications is paramount to improving outcomes. Association Rules Mining may support the discovery of those factors. In this work we propose a new approach, called Multi-target Association Rules Network (MTARN), to analyze association rules based on networks with a simultaneous focus on two parameters. The use of association rules networks aids the analysis of a high number of association rules and the multi-target strategy allows a complete exploration, explaining which factors directly influence the analyzed set. We evaluated our approach in conjunction with domain experts and compared it to two other approaches: Decision Trees and Filtered-ARNs, a single target approach based on networks for pattern visualization. The results indicates that MTARNs optimize the discovery of knowledge directly linked to complication and death factors in patients undergoing coronary artery bypass grafting. These parameters may be used in the construction of an intelligent monitoring system to aid myocardial revascularization patients. |
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Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networksIdentificação de fatores relacionados a complicações em cirurgia de revascularização do miocárdio: uma abordagem com redes de regras de associação multialvoIdentificación de factores relacionados con las complicaciones en la cirugía de injerto de derivación aortocoronaria: un enfoque con redes de reglas de asociación multiobjetivoReglas de asociaciónRedes de reglas de asociaciónCoronarioCirugía de bypass de la arteria coronariaProcesamiento de datosMultiobjetivo.Association rulesAssociation rules networksCoronaryCoronary artery bypass surgeryData miningMulti-targetMulti-target.Regras de associaçãoRedes de regras de associaçãoCoronáriaCirurgia de revascularização miocárdicaMineração de dadosMultialvo.Myocardial revascularization surgery is one of the recommended approaches for the treatment of chronic coronary disease. Several complications related to mortality, sequelae, length of stay, and hospital costs are also associated with this procedure. Death rates and complications depend on the characteristics of each patient. Knowing the factors related to hospital mortality and complications is paramount to improving outcomes. Association Rules Mining may support the discovery of those factors. In this work we propose a new approach, called Multi-target Association Rules Network (MTARN), to analyze association rules based on networks with a simultaneous focus on two parameters. The use of association rules networks aids the analysis of a high number of association rules and the multi-target strategy allows a complete exploration, explaining which factors directly influence the analyzed set. We evaluated our approach in conjunction with domain experts and compared it to two other approaches: Decision Trees and Filtered-ARNs, a single target approach based on networks for pattern visualization. The results indicates that MTARNs optimize the discovery of knowledge directly linked to complication and death factors in patients undergoing coronary artery bypass grafting. These parameters may be used in the construction of an intelligent monitoring system to aid myocardial revascularization patients.A cirurgia de revascularização miocárdica é uma das abordagens recomendadas para o tratamento da doença coronariana crônica. Várias complicações relacionadas à mortalidade, sequelas, tempo de internação e custos hospitalares também estão associadas a esse procedimento. As taxas de mortalidade e complicações dependem das características de cada paciente. Conhecer os fatores relacionados à mortalidade e complicações hospitalares é fundamental para melhorar os resultados. A mineração de regras de associação pode ajudar na descoberta desses fatores. Neste trabalho propomos uma nova abordagem, chamada Multi-target Association Rules Network (MTARN), para analisar regras de associação baseadas em redes com foco simultâneo em dois parâmetros. O uso de redes de regras de associação auxilia a análise de um grande número de regras de associação e a estratégia multialvo permite uma exploração completa, explicando quais fatores influenciam diretamente o conjunto analisado. Avaliamos nossa abordagem em conjunto com especialistas do domínio e a comparamos com duas outras abordagens: Árvores de Decisão e ARNs Filtrados, uma abordagem de destino único baseada em redes para visualização de padrões. Os resultados indicam que os MTARNs otimizam a descoberta de conhecimentos diretamente ligados a fatores de complicação e óbito em pacientes submetidos à cirurgia de revascularização do miocárdio. Esses parâmetros podem ser utilizados na construção de um sistema de monitoramento inteligente para auxiliar pacientes em revascularização miocárdica.La cirugía de revascularización miocárdica es uno de los abordajes recomendados para el tratamiento de la enfermedad coronaria crónica. Varias complicaciones relacionadas con la mortalidad, las secuelas, la estancia hospitalaria y los costos hospitalarios también se asocian con este procedimiento. Las tasas de mortalidad y complicaciones dependen de las características de cada paciente. Conocer los factores relacionados con la mortalidad hospitalaria y las complicaciones es fundamental para mejorar los resultados. La minería de reglas de asociación puede respaldar el descubrimiento de esos factores. En este trabajo proponemos un nuevo enfoque, llamado Multi-target Association Rules Network (MTARN), para analizar las reglas de asociación basadas en redes con un enfoque simultáneo en dos parámetros. El uso de redes de reglas de asociación ayuda al análisis de un gran número de reglas de asociación y la estrategia multiobjetivo permite una exploración completa, explicando qué factores influyen directamente en el conjunto analizado. Evaluamos nuestro enfoque junto con expertos en el dominio y lo comparamos con otros dos enfoques: árboles de decisión y ARN filtrados, un enfoque de objetivo único basado en redes para la visualización de patrones. Los resultados indican que los MTARN optimizan el descubrimiento de conocimiento directamente relacionado con los factores de complicación y muerte en pacientes sometidos a un injerto de derivación de la arteria coronaria. Estos parámetros pueden utilizarse en la construcción de un sistema de monitorización inteligente para ayudar a los pacientes con revascularización miocárdica.Research, Society and Development2022-11-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/3763810.33448/rsd-v11i15.37638Research, Society and Development; Vol. 11 No. 15; e506111537638Research, Society and Development; Vol. 11 Núm. 15; e506111537638Research, Society and Development; v. 11 n. 15; e5061115376382525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/37638/31235Copyright (c) 2022 Dario Brito Calçada; Cantídio de Moura Campos Neto; Vivian Lerner Amato; Roberta Akemi Sinoara ; Solange Oliveira Rezendehttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessCalçada, Dario BritoCampos Neto, Cantídio de MouraAmato, Vivian LernerSinoara , Roberta AkemiRezende, Solange Oliveira2022-11-27T19:56:23Zoai:ojs.pkp.sfu.ca:article/37638Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:51:43.948079Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks Identificação de fatores relacionados a complicações em cirurgia de revascularização do miocárdio: uma abordagem com redes de regras de associação multialvo Identificación de factores relacionados con las complicaciones en la cirugía de injerto de derivación aortocoronaria: un enfoque con redes de reglas de asociación multiobjetivo |
title |
Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks |
spellingShingle |
Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks Calçada, Dario Brito Reglas de asociación Redes de reglas de asociación Coronario Cirugía de bypass de la arteria coronaria Procesamiento de datos Multiobjetivo. Association rules Association rules networks Coronary Coronary artery bypass surgery Data mining Multi-target Multi-target. Regras de associação Redes de regras de associação Coronária Cirurgia de revascularização miocárdica Mineração de dados Multialvo. |
title_short |
Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks |
title_full |
Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks |
title_fullStr |
Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks |
title_full_unstemmed |
Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks |
title_sort |
Identification of factors related to complications in myocardial revascularization surgery: an approach with multi-target association rules networks |
author |
Calçada, Dario Brito |
author_facet |
Calçada, Dario Brito Campos Neto, Cantídio de Moura Amato, Vivian Lerner Sinoara , Roberta Akemi Rezende, Solange Oliveira |
author_role |
author |
author2 |
Campos Neto, Cantídio de Moura Amato, Vivian Lerner Sinoara , Roberta Akemi Rezende, Solange Oliveira |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Calçada, Dario Brito Campos Neto, Cantídio de Moura Amato, Vivian Lerner Sinoara , Roberta Akemi Rezende, Solange Oliveira |
dc.subject.por.fl_str_mv |
Reglas de asociación Redes de reglas de asociación Coronario Cirugía de bypass de la arteria coronaria Procesamiento de datos Multiobjetivo. Association rules Association rules networks Coronary Coronary artery bypass surgery Data mining Multi-target Multi-target. Regras de associação Redes de regras de associação Coronária Cirurgia de revascularização miocárdica Mineração de dados Multialvo. |
topic |
Reglas de asociación Redes de reglas de asociación Coronario Cirugía de bypass de la arteria coronaria Procesamiento de datos Multiobjetivo. Association rules Association rules networks Coronary Coronary artery bypass surgery Data mining Multi-target Multi-target. Regras de associação Redes de regras de associação Coronária Cirurgia de revascularização miocárdica Mineração de dados Multialvo. |
description |
Myocardial revascularization surgery is one of the recommended approaches for the treatment of chronic coronary disease. Several complications related to mortality, sequelae, length of stay, and hospital costs are also associated with this procedure. Death rates and complications depend on the characteristics of each patient. Knowing the factors related to hospital mortality and complications is paramount to improving outcomes. Association Rules Mining may support the discovery of those factors. In this work we propose a new approach, called Multi-target Association Rules Network (MTARN), to analyze association rules based on networks with a simultaneous focus on two parameters. The use of association rules networks aids the analysis of a high number of association rules and the multi-target strategy allows a complete exploration, explaining which factors directly influence the analyzed set. We evaluated our approach in conjunction with domain experts and compared it to two other approaches: Decision Trees and Filtered-ARNs, a single target approach based on networks for pattern visualization. The results indicates that MTARNs optimize the discovery of knowledge directly linked to complication and death factors in patients undergoing coronary artery bypass grafting. These parameters may be used in the construction of an intelligent monitoring system to aid myocardial revascularization patients. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11-24 |
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://rsdjournal.org/index.php/rsd/article/view/37638 10.33448/rsd-v11i15.37638 |
url |
https://rsdjournal.org/index.php/rsd/article/view/37638 |
identifier_str_mv |
10.33448/rsd-v11i15.37638 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/37638/31235 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 11 No. 15; e506111537638 Research, Society and Development; Vol. 11 Núm. 15; e506111537638 Research, Society and Development; v. 11 n. 15; e506111537638 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052774769229824 |