About: Multidimensional scaling analysis of virus diseases

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Multidimensional scaling analysis of virus diseases
Creator	Lopes, António Machado, J Andrade, José
Source	Elsevier; Medline; PMC
abstract	Abstract 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.
has issue date	2016-07-31(xsd:dateTime)
bibo:doi	10.1016/j.cmpb.2016.03.029
bibo:pmid	27265052
has license	els-covid
sha1sum (hex)	0c88cb2b06c8a313c0ac6ee8a320fdae3abecc26
schema:url	https://doi.org/10.1016/j.cmpb.2016.03.029
resource representing a document's title	Multidimensional scaling analysis of virus diseases
has PubMed Central identifier	PMC7114580
has PubMed identifier	27265052
schema:publication	Computer Methods and Programs in Biomedicine
resource representing a document's body	covid:0c88cb2b06c8a313c0ac6ee8a320fdae3abecc26#body_text
is schema:about of	named entity 'represent' named entity 'virus' named entity 'DESIGN' named entity 'PLETHORA' named entity 'STATISTICAL' named entity 'FEATURES' named entity 'HAVE' named entity 'INFECTIOUS AGENTS' named entity 'IMPORTANT' named entity 'INSIDE' named entity 'COMPUTATIONAL TECHNIQUES' named entity 'DISTINCT' named entity 'BUT' named entity 'HUGE' named entity 'ORGANISMS' named entity 'CONSEQUENCES' named entity 'REVEAL' named entity 'HANDLING' named entity 'SPREAD' named entity 'DATA' named entity 'ANALYSIS' named entity 'MULTIDIMENSIONAL SCALING' named entity 'REPLICATE' named entity 'BACKGROUND' named entity 'PUBLIC HEALTH' named entity 'CHARACTERISTICS' named entity 'AVAILABLE' named entity 'HIGHLIGHTING' named entity 'DANGER' named entity 'REPRESENT' named entity 'OBJECTIVE' named entity 'CAPABLE' named entity 'VIRAL INFECTIONS' named entity 'VIRUS DISEASES' named entity 'VIRUSES' covid:arg/0c88cb2b06c8a313c0ac6ee8a320fdae3abecc26 named entity 'replicate' named entity 'Viral infections' named entity 'replicate' named entity 'computational techniques' named entity 'Risk Group' named entity 'data structure' named entity 'pathologies' named entity 'algorithm' named entity 'common cold' named entity 'MDS' named entity 'correlation' named entity 'MDS' named entity 'MDS' named entity 'body fluids' named entity 'smallpox' named entity 'public health' named entity 'virus species' named entity 'MDS' named entity 'Lyssavirus' named entity 'MDS' named entity 'Canberra distance' named entity 'arthropods' named entity 'algorithm' named entity 'MDS' named entity 'locus' named entity 'objective function' named entity 'Risk Group' named entity 'Hepatitis' named entity 'MDS' named entity 'MDS' named entity 'therapeutic interventions' named entity 'Norovirus' named entity 'MDS' named entity 'human populations' named entity 'symmetric matrix' named entity 'algorithm' named entity 'mortality rates' named entity 'correlation' named entity 'infecting humans' named entity 'MDS' named entity 'MDS' named entity 'life-threatening disease' named entity 'viral illnesses'

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