Evidence map›Paper›PMID 41948483›Full record

Article... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics2024

Integrating Neuroimaging and Genetics via Contrastive Learning for Working Memory.

Pranav Nadigapu Suresh, Behnam Kazemivash, Dawn M Jensen, Vince Calhoun, Jingyu Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics, 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

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.

Pranav Nadigapu SureshComputer Science, Georgia State University, Atlanta, USA.ORCID 0000-0001-9167-3718
Behnam KazemivashComputer Science, Georgia State University, Atlanta, USA.
Dawn M JensenTReNDS, Georgia State University, Atlanta, USA.
Vince CalhounTReNDS, Georgis State university, Atlanta, USA.
Jingyu LiuComputer Science, Georgia State University, Atlanta, USA.

Funding

Flexible multivariate models for linking multi-scale connectome and genome data in Alzheimer's disease and related disordersRF1AG063153 · NIA · GEORGIA STATE UNIVERSITY · PI CALHOUN, VINCE D, LIU, JINGYU · 2019 to 2020
$3.5M
NIA NIH HHS RF1 AG063153
6 · The paper itself

Abstract

Understanding working memory's genetic and neural bases is crucial for advancing cognitive neuroscience and identifying biomarkers for cognitive impairments, particularly in the older population. This study integrates SNP and neuroimaging data from the UK biobank to improve the classification of high vs. low working memory capacity and reveal genetic factors associated with brain structure. 1060 SNPs belonging to Protein-Protein Interaction networks of amyloid precursor protein and

Indexed as

Contrastive learningGenetic variantsNeuroimagingSparse Canonical Correlation AnalysisWorking memory

Identifiers

PMID41948483
PMCPMC13051477

What OpenQuestion holds

Textmetadata
LicenceTDM
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.