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A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds

bioRxiv (Cold Spring Harbor Laboratory)(2024)10.1101/2024.05.16.594528Source: DataRank Database

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2024). On theSindex it has a DataRank of 0.

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Enrichment:Funding (9 grants)OA: greenTopics (13)IDs (PubMed)SDGs (1)

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Authors (10)

Gang Qu ORCID,Ziyu Zhou ORCID,Anqi Liu ORCID,Hong‐Wen Deng ORCID,Zhengming Ding ORCID

Live enrichment

PubMed:38798580

National Institutes of Health

Grant: 5R01MH107354-03

Integration of fMRI imaging, genomics, network and biological knowledge

National Institutes of Health

Grant: 5R01MH103220-04

Neurophysiological markers of HAND and the impact of aging: Evidence from MEG

National Institutes of Health

Grant: 3R01EB020407-02S1

Unified multivariate data-driven solutions for static and dynamic brain connectivity

National Science Foundation

Grant: 1539067

RII Track-2 FEC: Developmental Chronnecto-Genomics (Dev-CoG): A Next Generation Framework for Quantifying Brain Dynamics and Related Genetic Factors in Childhood

National Institutes of Health

Grant: 1P20GM144641-01

Center for Pediatric Brain Health

National Institutes of Health

Grant: 5R01GM109068-04

Integration of multiscale genomic data for comprehensive analysis of complex dise

National Institutes of Health

Grant: 5R01MH121101-06

DEVELOPMENTAL MULTIMODAL IMAGING OF NEUROCOGNITIVE DYNAMICS (DEV-MIND)

National Institutes of Health

Grant: 5U19AG055373-04

Trans-omics integration of multi-omics studies for male osteoporosis

National Institutes of Health

Grant: 5R01MH104680-03

Integration of brain imaging with genomic and epigenomic data

greenLicense: CC BY

GREENhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11118390

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2024/05/16/2024.05.16.594528.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2024.05.16.594528

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC11118598/pdf/nihpp-2405.07977v1.pdf

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/11118390

Fields of Study

BiologyMedicineComputer Science0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

FOS: Computer and information sciencesComputer Science - Machine LearningQuantitative Biology - Neurons and CognitionFOS: Biological sciencesNeurons and Cognition (q-bio.NC)Quantitative Biology - Quantitative MethodsQuantitative Methods (q-bio.QM)Machine Learning (cs.LG)

Sustainable Development Goals

SDG 3: 3. Good health