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Model and predict age and sex in healthy subjects using brain white matter features: A deep learning approach

arXiv (Cornell University)(2022)10.48550/arxiv.2202.03595Source: DataRank Database

Model and predict age and sex in healthy subjects using brain white matter features: A deep learning approach is a research paper published in arXiv (Cornell University) (2022). On theSindex it has a DataRank of 0.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)OA: greenTopics (28)IDs (PubMed, OpenAlex)SDGs (1)

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Authors (7)

Fan Zhang ORCID,Steve Pieper ORCID,Nikos Makris ORCID,Yogesh Rathi ORCID,William A. Wells ORCID

Live enrichment

PubMed:19022398 OpenAlex:https://openalex.org/W4294742220

National Institutes of Health

Grant: 5R01MH119222-03

Harmonizing multi-site diffusion MRI acquisitions for neuroscientific analysis across ages and brain disorders

National Institutes of Health

Grant: 1R01MH125860-01

Mapping the superficial white matter connectome of the human brain using ultra high resolution multi-contrast diffusion MRI

National Institutes of Health

Grant: 5P41EB015902-20

Neuroimaging Analysis Center (NAC)

greenLicense: cc-by

repositoryhttps://arxiv.org/pdf/2202.03595

repositoryhttp://arxiv.org/abs/2202.03595

repositoryhttps://doi.org/10.48550/arxiv.2202.03595

https://doi.org/10.1109/isbi52829.2022.9761684

https://dx.doi.org/10.48550/arxiv.2202.03595

Fields of Study

Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsImage and Video Processing (eess.IV)Computer Vision and Pattern Recognition (cs.CV)FOS: Electrical engineering, electronic engineering, information engineeringFOS: Computer and information sciences03 medical and health sciences0302 clinical medicine

Keywords

Fractional anisotropyHuman Connectome ProjectWhite matterDiffusion MRIConnectomeArtificial intelligencePsychologyComputer scienceMachine learningNeuroscienceMedicineFunctional connectivityMagnetic resonance imagingFOS: Computer and information sciencesComputer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)Computer Science - Computer Vision and Pattern RecognitionFOS: Electrical engineering, electronic engineering, information engineeringElectrical Engineering and Systems Science - Image and Video Processing

Sustainable Development Goals

SDG 3: 3. Good health