Evidence map›Paper›PMID 39279829›Full record

ArticleArXiv2024

Contrastive Graph Pooling for Explainable Classification of Brain Networks.

Jiaxing Xu, Qingtian Bian, Xinhang Li, Aihu Zhang, Yiping Ke, Miao Qiao, Wei Zhang, Wei Khang Jeremy Sim, Balázs Gulyás, Alzheimer’s Disease Neuroimaging Initiative

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2024. 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
–field-weighted citation impact
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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Jiaxing XuSchool of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798 Singapore.
Qingtian BianSchool of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798 Singapore.
Xinhang LiDepartment of Computer Science and Technology, Tsinghua University BEIJING, 100084 P.R.China.
Aihu ZhangSchool of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798 Singapore.
Yiping KeSchool of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798 Singapore.
Miao QiaoSchool of Computer Science, the University of Auckland, Auckland 1142 New Zealand.
Wei ZhangLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 636921 Singapore.
Wei Khang Jeremy SimLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 636921 Singapore.
Balázs GulyásLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 636921 Singapore.
Alzheimer’s Disease Neuroimaging Initiative

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

Functional magnetic resonance imaging (fMRI) is a commonly used technique to measure neural activation. Its application has been particularly important in identifying underlying neurodegenerative conditions such as Parkinson's, Alzheimer's, and Autism. Recent analysis of fMRI data models the brain as a graph and extracts features by graph neural networks (GNNs). However, the unique characteristics of fMRI data require a special design of GNN. Tailoring GNN to generate effective and domain-explainable features remains challenging. In this paper, we propose a contrastive dual-attention block and a differentiable graph pooling method called

Indexed as

Brain NetworkDeep Learning for NeuroimagingfMRI BiomarkerGraph ClassificationGraph Neural Network

Identifiers

PMID39279829
PMCPMC11398548

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.