ArticleComputer methods and programs in biomedicine2016
Multidimensional scaling analysis of virus diseases.
Article in Computer methods and programs in biomedicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed, 27 citations in OpenAlex.
- Visualization of cross-resistance between antimicrobial agents by asymmetric multidimensional scaling.Journal of clinical pharmacy and therapeutics · 2022Article
- In memory of Professor José António Tenreiro Machado (1957-2021).Nonlinear dynamics · 2022Article
- Advances in the computational analysis of SARS-COV2 genome.Nonlinear dynamics · 2021Article
- Computational analysis of the SARS-CoV-2 and other viruses based on the Kolmogorov's complexity and Shannon's information theories.Nonlinear dynamics · 2020Article
- Understanding COVID-19 nonlinear multi-scale dynamic spreading in Italy.Nonlinear dynamics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveViruses 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.
methodsThis 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.
resultsThe results are robust to uncertainties in the data and revealed to be consistent with clinical practice.
conclusionsThe 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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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.