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Logic programming and artificial neural networks in breast cancer detection

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Resumo:About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.
Autores principais:Neves, José
Outros Autores:Guimarães, Tiago; Gomes, Sabino; Vicente, Henrique; Santos, Mariana; Neves, João; Machado, José; Novais, Paulo
Assunto:Breast cancer Tyrer-cuzick model Knowledge representation and reasoning Logic programing Artificial Neural Networks
Ano:2015
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
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author Neves, José
author2 Guimarães, Tiago
Gomes, Sabino
Vicente, Henrique
Santos, Mariana
Neves, João
Machado, José
Novais, Paulo
author2_role author
author
author
author
author
author
author
author_facet Neves, José
Guimarães, Tiago
Gomes, Sabino
Vicente, Henrique
Santos, Mariana
Neves, João
Machado, José
Novais, Paulo
author_role author
contributor_name_str_mv Universidade do Minho
country_str PT
creators_json_txt [{\"Person.name\":\"Neves, José\"},{\"Person.name\":\"Guimarães, Tiago\"},{\"Person.name\":\"Gomes, Sabino\"},{\"Person.name\":\"Vicente, Henrique\"},{\"Person.name\":\"Santos, Mariana\"},{\"Person.name\":\"Neves, João\"},{\"Person.name\":\"Machado, José\"},{\"Person.name\":\"Novais, Paulo\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Universidade do Minho
datacite.creators.creator.creatorName.fl_str_mv Neves, José
Guimarães, Tiago
Gomes, Sabino
Vicente, Henrique
Santos, Mariana
Neves, João
Machado, José
Novais, Paulo
datacite.date.Accepted.fl_str_mv 2015-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2015-12-15T16:49:12Z
datacite.date.embargoed.fl_str_mv 2015-12-15T16:49:12Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Breast cancer
Tyrer-cuzick model
Knowledge representation and reasoning
Logic programing
Artificial Neural Networks
datacite.titles.title.fl_str_mv Logic programming and artificial neural networks in breast cancer detection
dc.contributor.none.fl_str_mv Universidade do Minho
dc.creator.none.fl_str_mv Neves, José
Guimarães, Tiago
Gomes, Sabino
Vicente, Henrique
Santos, Mariana
Neves, João
Machado, José
Novais, Paulo
dc.date.Accepted.fl_str_mv 2015-01-01T00:00:00Z
dc.date.available.fl_str_mv 2015-12-15T16:49:12Z
dc.date.embargoed.fl_str_mv 2015-12-15T16:49:12Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://hdl.handle.net/1822/39025
dc.language.none.fl_str_mv eng
dc.publisher.none.fl_str_mv Springer
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Breast cancer
Tyrer-cuzick model
Knowledge representation and reasoning
Logic programing
Artificial Neural Networks
dc.title.fl_str_mv Logic programming and artificial neural networks in breast cancer detection
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_5794
description About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.
dirty 0
eu_rights_str_mv openAccess
format conferencePaper
fulltext.url.fl_str_mv https://prod-dspace.uminho.pt/bitstreams/da2d4f64-9a1c-40bd-aacb-b2a2108a6be2/download
id rum_ad30606c8a4af87f3d7838427abd6c2f
identifier.url.fl_str_mv https://hdl.handle.net/1822/39025
instacron_str repositorium
institution Universidade do Minho
instname_str Universidade do Minho
language eng
network_acronym_str rum
network_name_str RepositóriUM - Universidade do Minho
oai_identifier_str oai:repositorium.uminho.pt:1822/39025
organization_str_mv urn:organizationAcronym:repositorium
person_str_mv Neves, José
Guimarães, Tiago
Gomes, Sabino
Vicente, Henrique
Santos, Mariana
Neves, João
Machado, José
Novais, Paulo
publishDate 2015
publisher.none.fl_str_mv Springer
reponame_str RepositóriUM - Universidade do Minho
repository_id_str urn:repositoryAcronym:rum
service_str_mv urn:repositoryAcronym:rum
spelling engSpringerporAbout 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.application/pdfporLogic programming and artificial neural networks in breast cancer detectionNeves, JoséGuimarães, TiagoGomes, SabinoVicente, HenriqueSantos, MarianaNeves, JoãoMachado, JoséNovais, PauloHostingInstitutionOrganizationalUniversidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptISBNIsPartOf9783319192215ISSNIsPartOf0302-9743DOIIsPartOf10.1007/978-3-319-19222-2_182015-12-15T16:49:12Z20152015-12-10T17:48:03Z2015-01-01T00:00:00ZHandlehttps://hdl.handle.net/1822/39025http://purl.org/coar/access_right/c_abf2open accessBreast cancerTyrer-cuzick modelKnowledge representation and reasoningLogic programingArtificial Neural Networks277619 bytesother research producthttp://purl.org/coar/resource_type/c_5794conference paperhttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://prod-dspace.uminho.pt/bitstreams/da2d4f64-9a1c-40bd-aacb-b2a2108a6be2/download
spellingShingle Logic programming and artificial neural networks in breast cancer detection
Neves, José
Breast cancer
Tyrer-cuzick model
Knowledge representation and reasoning
Logic programing
Artificial Neural Networks
status SINGLETON
subject.fl_str_mv Breast cancer
Tyrer-cuzick model
Knowledge representation and reasoning
Logic programing
Artificial Neural Networks
title Logic programming and artificial neural networks in breast cancer detection
title_full Logic programming and artificial neural networks in breast cancer detection
title_fullStr Logic programming and artificial neural networks in breast cancer detection
title_full_unstemmed Logic programming and artificial neural networks in breast cancer detection
title_short Logic programming and artificial neural networks in breast cancer detection
title_sort Logic programming and artificial neural networks in breast cancer detection
topic Breast cancer
Tyrer-cuzick model
Knowledge representation and reasoning
Logic programing
Artificial Neural Networks
topic_facet Breast cancer
Tyrer-cuzick model
Knowledge representation and reasoning
Logic programing
Artificial Neural Networks
url https://hdl.handle.net/1822/39025
visible 1