2017
DOI: 10.20944/preprints201710.0018.v1
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Challenges and Opportunities for Visualization and Analysis of Graph-Modeled Medical Data

Abstract: Graphs are largely used in computer science to model relations, or associations, among entities the compose complex systems. More recently, they found a broad field of application in bioinformatics and medical informatics supporting modelling, analysis of many systems. The applications span from representing interactions among molecules within cells, to model the functions of the brains. In order to support research, algorithms from graph theory that are able to extract knowledge from network should be coupled… Show more

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Cited by 4 publications
(3 citation statements)
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“…Thus, we mapped each similarity matrix M ( i , j ) into a network N (Agapito et al. 2017 ). The nodes are the Italian regions, and the edges link two regions ( i , j ) when the p value is greater than the threshold, otherwise ( p value < 0.05) no edge is added.…”
Section: Cctv Methodologymentioning
confidence: 99%
“…Thus, we mapped each similarity matrix M ( i , j ) into a network N (Agapito et al. 2017 ). The nodes are the Italian regions, and the edges link two regions ( i , j ) when the p value is greater than the threshold, otherwise ( p value < 0.05) no edge is added.…”
Section: Cctv Methodologymentioning
confidence: 99%
“…In order to evaluate the evolution of Italian COVID-19 data and evidence which regions show similar trend, we built networks of each data [1] starting from the result of Wilcoxon test. The nodes of the networks are the Italian regions and the edges link two regions (nodes) with similar trend according to significance level (p-value > 0.05) obtained from Wilcoxon test, otherwise (p-value < 0.05) there is not connection among nodes.…”
Section: Network-based Analysismentioning
confidence: 99%
“…To evaluate the evolution of Italian COVID-19 data and evidence which regions show similar behavior, we built networks of each piece of data [10] starting from the result of Wilcoxon test. The nodes of the networks are the Italian regions and the edges link two regions (nodes) with similar trend according to significance level (p-value > 0.05) obtained from the Wilcoxon test, otherwise (p-value < 0.05) there is not connection among nodes.…”
Section: Mapping Similarity Matrices To Networkmentioning
confidence: 99%