Investigating Community Detection Algorithms and their Capacity as Markers of Brain Diseases

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00098154" target="_blank" >RIV/00216224:14330/17:00098154 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.22323/1.293.0018" target="_blank" >http://dx.doi.org/10.22323/1.293.0018</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.22323/1.293.0018" target="_blank" >10.22323/1.293.0018</a>

Result language

angličtina

Original language name

Investigating Community Detection Algorithms and their Capacity as Markers of Brain Diseases

Original language description

In this paper, we present a workflow for evaluating resting-state brain functional connectivity with different community detection algorithms and their strengths to discriminate between health and Parkinson’s disease (PD) and mild cognitive impairment preceding Alzheimer’s disease (ADMCI). We further analyze the complexity of particular pipeline steps aiming to provide guidelines for both execution on computing infrastructure and further optimization efforts. On a dataset of 50 controls and 70 patients we measured an increased modularity coefficient with 81.8% accuracy of classifying PD versus controls and 76.2% accuracy of classifying ADMCI versus controls. Significantly higher modularity coefficient values were measured when the random matrix theory decomposition was adapted for network construction. These results were observed on networks of 82 nodes based on AAL atlas and 317 nodes based on multimodal parcellation atlas.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

International Symposium on Grids and Clouds (ISGC) 2017. Academia Sinica, Taipei, Taiwan: Proceedings of Science

ISBN

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ISSN

1824-8039

e-ISSN

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Number of pages

14

Pages from-to

1-14

Publisher name

Sissa Medialab Srl

Place of publication

Taipei; Taiwan

Event location

Taipei; Taiwan

Event date

Jan 1, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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