Multidimensional scaling analysis of virus diseases

Detalhes bibliográficos
Autor(a) principal: Lopes, António M.
Data de Publicação: 2016
Outros Autores: Andrade, José P., Machado, J.A.Tenreiro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/9413
Resumo: Background and Objective: Viruses are infectious agents that replicate inside organisms and reveal a plethora of distinct characteristics.Viral infections spread in many ways, but often have devastating consequences and represent a huge danger for public health. It is important to design statistical and computational techniques capable of handling the available data and highlighting the most important features. Methods: This paper reviews the quantitative and qualitative behaviour of 22 infectious diseases caused by viruses. The information is compared and visualized by means of the multidimensional scaling technique. Results: The results are robust to uncertainties in the data and revealed to be consistent with clinical practice. Conclusions: The paper shows that the proposed methodology may represent a solid mathematical tool to tackle a larger number of virus and additional information about these infectious agents.
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spelling Multidimensional scaling analysis of virus diseasesMultidimensional scalingClusteringVirus diseasesBackground and Objective: Viruses are infectious agents that replicate inside organisms and reveal a plethora of distinct characteristics.Viral infections spread in many ways, but often have devastating consequences and represent a huge danger for public health. It is important to design statistical and computational techniques capable of handling the available data and highlighting the most important features. Methods: This paper reviews the quantitative and qualitative behaviour of 22 infectious diseases caused by viruses. The information is compared and visualized by means of the multidimensional scaling technique. Results: The results are robust to uncertainties in the data and revealed to be consistent with clinical practice. Conclusions: The paper shows that the proposed methodology may represent a solid mathematical tool to tackle a larger number of virus and additional information about these infectious agents.ElsevierRepositório Científico do Instituto Politécnico do PortoLopes, António M.Andrade, José P.Machado, J.A.Tenreiro20162117-01-01T00:00:00Z2016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/9413enghttp://dx.doi.org/10.1016/j.cmpb.2016.03.029metadata only accessinfo: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:RCAAP2023-03-13T12:50:47Zoai:recipp.ipp.pt:10400.22/9413Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:30:00.925707Repositório 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 Multidimensional scaling analysis of virus diseases
title Multidimensional scaling analysis of virus diseases
spellingShingle Multidimensional scaling analysis of virus diseases
Lopes, António M.
Multidimensional scaling
Clustering
Virus diseases
title_short Multidimensional scaling analysis of virus diseases
title_full Multidimensional scaling analysis of virus diseases
title_fullStr Multidimensional scaling analysis of virus diseases
title_full_unstemmed Multidimensional scaling analysis of virus diseases
title_sort Multidimensional scaling analysis of virus diseases
author Lopes, António M.
author_facet Lopes, António M.
Andrade, José P.
Machado, J.A.Tenreiro
author_role author
author2 Andrade, José P.
Machado, J.A.Tenreiro
author2_role author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Lopes, António M.
Andrade, José P.
Machado, J.A.Tenreiro
dc.subject.por.fl_str_mv Multidimensional scaling
Clustering
Virus diseases
topic Multidimensional scaling
Clustering
Virus diseases
description Background and Objective: Viruses are infectious agents that replicate inside organisms and reveal a plethora of distinct characteristics.Viral infections spread in many ways, but often have devastating consequences and represent a huge danger for public health. It is important to design statistical and computational techniques capable of handling the available data and highlighting the most important features. Methods: This paper reviews the quantitative and qualitative behaviour of 22 infectious diseases caused by viruses. The information is compared and visualized by means of the multidimensional scaling technique. Results: The results are robust to uncertainties in the data and revealed to be consistent with clinical practice. Conclusions: The paper shows that the proposed methodology may represent a solid mathematical tool to tackle a larger number of virus and additional information about these infectious agents.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-01-01T00:00:00Z
2117-01-01T00:00:00Z
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