Evidence map›Paper›PMID 31828105›Full record

ArticleBioMed research international2019

Finding Community Modules of Brain Networks Based on PSO with Uniform Design.

Jie Zhang, Lingkai Tang, Bo Liao, Xiaoshu Zhu, Fang-Xiang Wu

Abstract read
In one paragraph

Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Jie ZhangSchool of Computer Science and Engineering, Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data Processing, Yulin Normal University, Yulin 537000, Guangxi, China.ORCID https://orcid.org/0000-0002-1078-1766
Lingkai TangDivision of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Sakatoon S7N5A9, Saskatchewan, Canada.
Bo LiaoDivision of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Sakatoon S7N5A9, Saskatchewan, Canada.ORCID https://orcid.org/0000-0001-7391-4063
Xiaoshu ZhuSchool of Computer Science and Engineering, Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data Processing, Yulin Normal University, Yulin 537000, Guangxi, China.ORCID https://orcid.org/0000-0002-7696-9112
Fang-Xiang WuDivision of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Sakatoon S7N5A9, Saskatchewan, Canada.ORCID https://orcid.org/0000-0002-4593-9332

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The brain has the most complex structures and functions in living organisms, and brain networks can provide us an effective way for brain function analysis and brain disease detection. In brain networks, there exist some important neural unit modules, which contain many meaningful biological insights. It is appealing to find the neural unit modules and obtain their affiliations. In this study, we present a novel method by integrating the uniform design into the particle swarm optimization to find community modules of brain networks, abbreviated as UPSO. The difference between UPSO and the existing ones lies in that UPSO is presented first for detecting community modules. Several brain networks generated from functional MRI for studying autism are used to verify the proposed algorithm. Experimental results obtained on these brain networks demonstrate that UPSO can find community modules efficiently and outperforms the other competing methods in terms of modularity and conductance. Additionally, the comparison of UPSO and PSO also shows that the uniform design plays an important role in improving the performance of UPSO.

Indexed as

Models, NeurologicalAlgorithmsBrainComputational BiologyHumansMagnetic Resonance ImagingNerve Net

Identifiers

PMID31828105
PMCPMC6885845

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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.