Chest Breadths to Predict Individuals' Age - A Case Based View

Detalhes bibliográficos
Autor(a) principal: Domingues, Andréa
Data de Publicação: 2016
Outros Autores: Vicente, Henrique, Neves, João, Alves, Victor, 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/10174/19693
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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spelling 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
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dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
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