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Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information
This paper addresses the visualization of complex information using multidimensional scaling (MDS). MDS is a technique adopted for processing data with multiple features scattered in high-dimensional spaces. For illustrating the proposed techniques, the case of viral diseases is considered. The stud...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7090701/ https://www.ncbi.nlm.nih.gov/pubmed/28391493 http://dx.doi.org/10.1007/s12539-017-0229-4 |
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author | Lopes, António M. Machado, J. A. Tenreiro Galhano, Alexandra M. |
author_facet | Lopes, António M. Machado, J. A. Tenreiro Galhano, Alexandra M. |
author_sort | Lopes, António M. |
collection | PubMed |
description | This paper addresses the visualization of complex information using multidimensional scaling (MDS). MDS is a technique adopted for processing data with multiple features scattered in high-dimensional spaces. For illustrating the proposed techniques, the case of viral diseases is considered. The study evaluates the characteristics of 21 viruses in the perspective of clinical information. Several new schemes are proposed for improving the visualization of the MDS charts. The results follow standard clinical practice, proving that the method represents a valuable tool to study a large number of viruses. |
format | Online Article Text |
id | pubmed-7090701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-70907012020-03-24 Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information Lopes, António M. Machado, J. A. Tenreiro Galhano, Alexandra M. Interdiscip Sci Original Research Article This paper addresses the visualization of complex information using multidimensional scaling (MDS). MDS is a technique adopted for processing data with multiple features scattered in high-dimensional spaces. For illustrating the proposed techniques, the case of viral diseases is considered. The study evaluates the characteristics of 21 viruses in the perspective of clinical information. Several new schemes are proposed for improving the visualization of the MDS charts. The results follow standard clinical practice, proving that the method represents a valuable tool to study a large number of viruses. Springer Berlin Heidelberg 2017-04-08 2019 /pmc/articles/PMC7090701/ /pubmed/28391493 http://dx.doi.org/10.1007/s12539-017-0229-4 Text en © Springer-Verlag 2017 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Article Lopes, António M. Machado, J. A. Tenreiro Galhano, Alexandra M. Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information |
title | Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information |
title_full | Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information |
title_fullStr | Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information |
title_full_unstemmed | Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information |
title_short | Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information |
title_sort | computational comparison and visualization of viruses in the perspective of clinical information |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7090701/ https://www.ncbi.nlm.nih.gov/pubmed/28391493 http://dx.doi.org/10.1007/s12539-017-0229-4 |
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