Evidence map›Paper›PMID 33140610›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2020

[Brain functional network reconstruction based on compressed sensing and fast iterative shrinkage-thresholding algorithm].

Qing Guo, Yueyang Teng, Can Tong, Disen Li, Xuefei Wang

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 48% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Qing GuoCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, P.R.China;Key Laboratory for Medical Imaging Intelligent Computing of Ministry of Education, Shenyang 110169, P.R.China.
Yueyang TengCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, P.R.China;Key Laboratory for Medical Imaging Intelligent Computing of Ministry of Education, Shenyang 110169, P.R.China.
Can TongCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, P.R.China;Key Laboratory for Medical Imaging Intelligent Computing of Ministry of Education, Shenyang 110169, P.R.China.
Disen LiCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, P.R.China.
Xuefei WangCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, P.R.China.
Northeastern University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The construction of brain functional network based on resting-state functional magnetic resonance imaging (fMRI) is an effective method to reveal the mechanism of human brain operation, but the common brain functional network generally contains a lot of noise, which leads to wrong analysis results. In this paper, the least absolute shrinkage and selection operator (LASSO) model in compressed sensing is used to reconstruct the brain functional network. This model uses the sparsity of

Indexed as

AlgorithmsImage Processing, Computer-AssistedBrainHumansMagnetic Resonance Imagingbrain functional networkcompressed sensingfast iterative shrinkage-thresholding algorithmleast absolute shrinkage and selection operator

Identifiers

PMID33140610
PMCPMC10320527
OpenAlexW3095028752

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.