Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Bruno
Data de Publicação: 2014
Outros Autores: Gomes, Sabino, Vicente, Henrique, Abelha, António, Novais, Paulo, Machado, José, Neves, José
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/12104
Resumo: On the one hand, cardiovascular diseases have severe consequences on an individual and for the society in general, once they are the main cause to death. These facts reveal that it is vital to get preventive, by knowing how probable is to have that kind of illness. On the other hand, and until now, this risk has been assessed by a Systematic Coronary Risk Evaluation procedure that takes data from charts based on gender, age, total cholesterol, systolic blood pressure and smoking status, but with no conceivable potential to deal with the incomplete or default data that is presented on those tools. Therefore, the focus in this work will be on the development of a risk evaluation support system based on a low-risk record, grounded on a new approach to knowledge representation and reasoning, that based on an extension to the Logic Programming language, will be able to overcome the drawbacks of the present ones. This will be complemented with a computational framework based on Artificial Neural Networks.
id RCAP_eb9dc931e1061230abe947cc6563390b
oai_identifier_str oai:dspace.uevora.pt:10174/12104
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Systematic Coronary Risk Evaluation through Artificial Neural Networks based SystemsSystematic Coronary Risk EvaluationKnowledge Representation and ReasoningLogic ProgrammingArtificial Neural NetworksOn the one hand, cardiovascular diseases have severe consequences on an individual and for the society in general, once they are the main cause to death. These facts reveal that it is vital to get preventive, by knowing how probable is to have that kind of illness. On the other hand, and until now, this risk has been assessed by a Systematic Coronary Risk Evaluation procedure that takes data from charts based on gender, age, total cholesterol, systolic blood pressure and smoking status, but with no conceivable potential to deal with the incomplete or default data that is presented on those tools. Therefore, the focus in this work will be on the development of a risk evaluation support system based on a low-risk record, grounded on a new approach to knowledge representation and reasoning, that based on an extension to the Logic Programming language, will be able to overcome the drawbacks of the present ones. This will be complemented with a computational framework based on Artificial Neural Networks.International Society of Computers and their Applications - ISCA2014-12-29T17:38:59Z2014-12-292014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/12104http://hdl.handle.net/10174/12104engRodrigues, B., Gomes, S., Vicente, H., Abelha, A., Novais, P., Machado, J., & Neves, J., Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems. In T. Goto Ed., Proceedings of the 27th International Conference on Computer Applications in Industry and Engineering (CAINE 2014), pp. 21–26, International Society of Computers and their Applications - ISCA, Winona, USA, 2014.21-26978–1–880843-97-0Departamento de Químicaa63318@alunos.uminho.ptsabinogomes.antonio@gmail.comhvicente@uevora.ptabelha@di.uminho.ptpjon@di.uminho.ptjmac@di.uminho.ptjneves@di.uminho.ptProceedings of the 27th International Conference on Computer Applications in Industry and Engineering (CAINE 2014)232Rodrigues, BrunoGomes, SabinoVicente, HenriqueAbelha, AntónioNovais, PauloMachado, JoséNeves, Joséinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T18:56:08Zoai:dspace.uevora.pt:10174/12104Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:05:36.960482Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems
title Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems
spellingShingle Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems
Rodrigues, Bruno
Systematic Coronary Risk Evaluation
Knowledge Representation and Reasoning
Logic Programming
Artificial Neural Networks
title_short Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems
title_full Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems
title_fullStr Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems
title_full_unstemmed Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems
title_sort Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems
author Rodrigues, Bruno
author_facet Rodrigues, Bruno
Gomes, Sabino
Vicente, Henrique
Abelha, António
Novais, Paulo
Machado, José
Neves, José
author_role author
author2 Gomes, Sabino
Vicente, Henrique
Abelha, António
Novais, Paulo
Machado, José
Neves, José
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Rodrigues, Bruno
Gomes, Sabino
Vicente, Henrique
Abelha, António
Novais, Paulo
Machado, José
Neves, José
dc.subject.por.fl_str_mv Systematic Coronary Risk Evaluation
Knowledge Representation and Reasoning
Logic Programming
Artificial Neural Networks
topic Systematic Coronary Risk Evaluation
Knowledge Representation and Reasoning
Logic Programming
Artificial Neural Networks
description On the one hand, cardiovascular diseases have severe consequences on an individual and for the society in general, once they are the main cause to death. These facts reveal that it is vital to get preventive, by knowing how probable is to have that kind of illness. On the other hand, and until now, this risk has been assessed by a Systematic Coronary Risk Evaluation procedure that takes data from charts based on gender, age, total cholesterol, systolic blood pressure and smoking status, but with no conceivable potential to deal with the incomplete or default data that is presented on those tools. Therefore, the focus in this work will be on the development of a risk evaluation support system based on a low-risk record, grounded on a new approach to knowledge representation and reasoning, that based on an extension to the Logic Programming language, will be able to overcome the drawbacks of the present ones. This will be complemented with a computational framework based on Artificial Neural Networks.
publishDate 2014
dc.date.none.fl_str_mv 2014-12-29T17:38:59Z
2014-12-29
2014-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/12104
http://hdl.handle.net/10174/12104
url http://hdl.handle.net/10174/12104
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Rodrigues, B., Gomes, S., Vicente, H., Abelha, A., Novais, P., Machado, J., & Neves, J., Systematic Coronary Risk Evaluation through Artificial Neural Networks based Systems. In T. Goto Ed., Proceedings of the 27th International Conference on Computer Applications in Industry and Engineering (CAINE 2014), pp. 21–26, International Society of Computers and their Applications - ISCA, Winona, USA, 2014.
21-26
978–1–880843-97-0
Departamento de Química
a63318@alunos.uminho.pt
sabinogomes.antonio@gmail.com
hvicente@uevora.pt
abelha@di.uminho.pt
pjon@di.uminho.pt
jmac@di.uminho.pt
jneves@di.uminho.pt
Proceedings of the 27th International Conference on Computer Applications in Industry and Engineering (CAINE 2014)
232
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv International Society of Computers and their Applications - ISCA
publisher.none.fl_str_mv International Society of Computers and their Applications - ISCA
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799136541461708800

Registros relacionados