Chest Breadths to Predict Individuals' Age - A Case Based View
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/19693 https://doi.org/10.1109/CBI.2016.50 |
Resumo: | It is well known that rib cage dimensions depend on the gender and vary with the age of the individual. Under this setting it is therefore possible to assume that a computational approach to the problem may be thought out and, consequently, this work will focus on the development of an Artificial Intelligence grounded decision support system to predict individual’s age, based on such measurements. On the one hand, using some basic image processing techniques it were extracted such descriptions from chest X-rays (i.e., its maximum width and height). On the other hand, the computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters for the handling of incomplete, unknown, or even contradictory information. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process. The accuracy of the proposed model is satisfactory, close to 90%. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Chest Breadths to Predict Individuals' Age - A Case Based ViewIntelligent SystemsChest X-ray ImagesLogic ProgrammingKnowledge RepresentationCase-Based ReasoningIt is well known that rib cage dimensions depend on the gender and vary with the age of the individual. Under this setting it is therefore possible to assume that a computational approach to the problem may be thought out and, consequently, this work will focus on the development of an Artificial Intelligence grounded decision support system to predict individual’s age, based on such measurements. On the one hand, using some basic image processing techniques it were extracted such descriptions from chest X-rays (i.e., its maximum width and height). On the other hand, the computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters for the handling of incomplete, unknown, or even contradictory information. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process. The accuracy of the proposed model is satisfactory, close to 90%.IEEE2017-01-10T15:38:27Z2017-01-102016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/19693http://hdl.handle.net/10174/19693https://doi.org/10.1109/CBI.2016.50engDomingues, A., Vicente, H., Neves, J., Alves, V. & Neves, J., Chest Breadths to Predict Individuals’ Age – A Case Based View. In E. Kornyshova, G. Poels & C. Huemer, Eds., Proceedings of the 18th IEEE Conference on Business Informatics, (CBI 2016) – Vol. 2, pp. 53–60, IEEE Edition, 2016.8978-1-5090-3231-0andrea.domingues.1993@gmail.comhvicente@uevora.ptjoaocpneves@gmail.comvalves@di.uminho.ptjneves@di.uminho.ptDomingues, AndréaVicente, HenriqueNeves, JoãoAlves, VictorNeves, 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:RCAAP2024-01-03T19:07:39Zoai:dspace.uevora.pt:10174/19693Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:10:44.034558Repositório 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 |
Chest Breadths to Predict Individuals' Age - A Case Based View |
title |
Chest Breadths to Predict Individuals' Age - A Case Based View |
spellingShingle |
Chest Breadths to Predict Individuals' Age - A Case Based View Domingues, Andréa Intelligent Systems Chest X-ray Images Logic Programming Knowledge Representation Case-Based Reasoning |
title_short |
Chest Breadths to Predict Individuals' Age - A Case Based View |
title_full |
Chest Breadths to Predict Individuals' Age - A Case Based View |
title_fullStr |
Chest Breadths to Predict Individuals' Age - A Case Based View |
title_full_unstemmed |
Chest Breadths to Predict Individuals' Age - A Case Based View |
title_sort |
Chest Breadths to Predict Individuals' Age - A Case Based View |
author |
Domingues, Andréa |
author_facet |
Domingues, Andréa Vicente, Henrique Neves, João Alves, Victor Neves, José |
author_role |
author |
author2 |
Vicente, Henrique Neves, João Alves, Victor Neves, José |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Domingues, Andréa Vicente, Henrique Neves, João Alves, Victor Neves, José |
dc.subject.por.fl_str_mv |
Intelligent Systems Chest X-ray Images Logic Programming Knowledge Representation Case-Based Reasoning |
topic |
Intelligent Systems Chest X-ray Images Logic Programming Knowledge Representation Case-Based Reasoning |
description |
It is well known that rib cage dimensions depend on the gender and vary with the age of the individual. Under this setting it is therefore possible to assume that a computational approach to the problem may be thought out and, consequently, this work will focus on the development of an Artificial Intelligence grounded decision support system to predict individual’s age, based on such measurements. On the one hand, using some basic image processing techniques it were extracted such descriptions from chest X-rays (i.e., its maximum width and height). On the other hand, the computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters for the handling of incomplete, unknown, or even contradictory information. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process. The accuracy of the proposed model is satisfactory, close to 90%. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01T00:00:00Z 2017-01-10T15:38:27Z 2017-01-10 |
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/10174/19693 http://hdl.handle.net/10174/19693 https://doi.org/10.1109/CBI.2016.50 |
url |
http://hdl.handle.net/10174/19693 https://doi.org/10.1109/CBI.2016.50 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Domingues, A., Vicente, H., Neves, J., Alves, V. & Neves, J., Chest Breadths to Predict Individuals’ Age – A Case Based View. In E. Kornyshova, G. Poels & C. Huemer, Eds., Proceedings of the 18th IEEE Conference on Business Informatics, (CBI 2016) – Vol. 2, pp. 53–60, IEEE Edition, 2016. 8 978-1-5090-3231-0 andrea.domingues.1993@gmail.com hvicente@uevora.pt joaocpneves@gmail.com valves@di.uminho.pt 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 |
IEEE |
publisher.none.fl_str_mv |
IEEE |
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 |
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1799136589388972032 |