A Case-based Approach to Colorectal Cancer Detection
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
DOI: | 10.1007/978-981-10-4154-9_50 |
Texto Completo: | http://hdl.handle.net/10174/22186 https://doi.org/10.1007/978-981-10-4154-9_50 |
Resumo: | Colorectal cancer is one of the most common malignancies in developed countries. Although it is not well known what causes this type of cancer, studies have showed that there are certain risk factors associated that may increase the likelihood of developing such malignancy. These factors comprise, among others, individual's age, lifestyle habits, personal disease history, and genetic syndromes. Despite its high mortality, colorectal cancer may be prevented with an early diagnosis. Thus, this work aims at the development of Artificial Intelligence based decision support system to assess the risk of developing colorectal cancer. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case-based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory data, information or knowledge. |
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A Case-based Approach to Colorectal Cancer DetectionColorectal CancerKnowledge Representation and ReasoningLogic ProgrammingCase-Based ReasoningDecision Support SystemsColorectal cancer is one of the most common malignancies in developed countries. Although it is not well known what causes this type of cancer, studies have showed that there are certain risk factors associated that may increase the likelihood of developing such malignancy. These factors comprise, among others, individual's age, lifestyle habits, personal disease history, and genetic syndromes. Despite its high mortality, colorectal cancer may be prevented with an early diagnosis. Thus, this work aims at the development of Artificial Intelligence based decision support system to assess the risk of developing colorectal cancer. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case-based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory data, information or knowledge.Springer2018-02-14T12:51:46Z2018-02-142017-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/22186http://hdl.handle.net/10174/22186https://doi.org/10.1007/978-981-10-4154-9_50engMorgado, P., Vicente, H., Abelha, A., Machado, J., Neves, J. & Neves, J., A Case-Based Approach to Colorectal Cancer Detection. Lecture Notes in Electrical Engineering, 424, 433–442, 2017.1876-1100 (paper)1876-1119 (electronic)http://link.springer.com/chapter/10.1007/978-981-10-4154-9_50pedrommcs@hotmail.comhvicente@uevora.ptabelha@di.uminho.ptjmac@di.uminho.ptjoaocpneves@gmail.comjneves@di.uminho.ptMorgado, PedroVicente, HenriqueAbelha, AntónioMachado, JoséNeves, JoãoNeves, 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:RCAAP2024-01-03T19:13:23Zoai:dspace.uevora.pt:10174/22186Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:13:17.511680Repositório 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 |
A Case-based Approach to Colorectal Cancer Detection |
title |
A Case-based Approach to Colorectal Cancer Detection |
spellingShingle |
A Case-based Approach to Colorectal Cancer Detection A Case-based Approach to Colorectal Cancer Detection Morgado, Pedro Colorectal Cancer Knowledge Representation and Reasoning Logic Programming Case-Based Reasoning Decision Support Systems Morgado, Pedro Colorectal Cancer Knowledge Representation and Reasoning Logic Programming Case-Based Reasoning Decision Support Systems |
title_short |
A Case-based Approach to Colorectal Cancer Detection |
title_full |
A Case-based Approach to Colorectal Cancer Detection |
title_fullStr |
A Case-based Approach to Colorectal Cancer Detection A Case-based Approach to Colorectal Cancer Detection |
title_full_unstemmed |
A Case-based Approach to Colorectal Cancer Detection A Case-based Approach to Colorectal Cancer Detection |
title_sort |
A Case-based Approach to Colorectal Cancer Detection |
author |
Morgado, Pedro |
author_facet |
Morgado, Pedro Morgado, Pedro Vicente, Henrique Abelha, António Machado, José Neves, João Neves, José Vicente, Henrique Abelha, António Machado, José Neves, João Neves, José |
author_role |
author |
author2 |
Vicente, Henrique Abelha, António Machado, José Neves, João Neves, José |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Morgado, Pedro Vicente, Henrique Abelha, António Machado, José Neves, João Neves, José |
dc.subject.por.fl_str_mv |
Colorectal Cancer Knowledge Representation and Reasoning Logic Programming Case-Based Reasoning Decision Support Systems |
topic |
Colorectal Cancer Knowledge Representation and Reasoning Logic Programming Case-Based Reasoning Decision Support Systems |
description |
Colorectal cancer is one of the most common malignancies in developed countries. Although it is not well known what causes this type of cancer, studies have showed that there are certain risk factors associated that may increase the likelihood of developing such malignancy. These factors comprise, among others, individual's age, lifestyle habits, personal disease history, and genetic syndromes. Despite its high mortality, colorectal cancer may be prevented with an early diagnosis. Thus, this work aims at the development of Artificial Intelligence based decision support system to assess the risk of developing colorectal cancer. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case-based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory data, information or knowledge. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01T00:00:00Z 2018-02-14T12:51:46Z 2018-02-14 |
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/10174/22186 http://hdl.handle.net/10174/22186 https://doi.org/10.1007/978-981-10-4154-9_50 |
url |
http://hdl.handle.net/10174/22186 https://doi.org/10.1007/978-981-10-4154-9_50 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Morgado, P., Vicente, H., Abelha, A., Machado, J., Neves, J. & Neves, J., A Case-Based Approach to Colorectal Cancer Detection. Lecture Notes in Electrical Engineering, 424, 433–442, 2017. 1876-1100 (paper) 1876-1119 (electronic) http://link.springer.com/chapter/10.1007/978-981-10-4154-9_50 pedrommcs@hotmail.com hvicente@uevora.pt abelha@di.uminho.pt jmac@di.uminho.pt joaocpneves@gmail.com jneves@di.uminho.pt |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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 |
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1822228298505125888 |
dc.identifier.doi.none.fl_str_mv |
10.1007/978-981-10-4154-9_50 |