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Reliability and predictability of phenotype information from functional connectivity in large imaging datasets.

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Title: Reliability and predictability of phenotype information from functional connectivity in large imaging datasets.
Authors: Dafflon J; Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA.; Machine Learning Team, National Institute of Mental Health, Bethesda, MD, USA., Moraczewski D; Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA., Earl E; Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA., Nielson DM; Machine Learning Team, National Institute of Mental Health, Bethesda, MD, USA., Loewinger G; Machine Learning Team, National Institute of Mental Health, Bethesda, MD, USA., McClure P; Naval Postgraduate School, Monterey, CA, USA., Thomas AG; Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA., Pereira F; Machine Learning Team, National Institute of Mental Health, Bethesda, MD, USA.
Source: ArXiv [ArXiv] 2024 May 01. Date of Electronic Publication: 2024 May 01.
Publication Type: Preprint; Journal Article
Journal Info: Country of Publication: United States NLM ID: 101759493 Publication Model: Electronic Cited Medium: Internet ISSN: 2331-8422 (Electronic) Linking ISSN: 23318422 NLM ISO Abbreviation: ArXiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 38745697
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Reliability and predictability of phenotype information from functional connectivity in large imaging datasets.
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  Data: <searchLink fieldCode="AU" term="%22Dafflon+J%22">Dafflon J</searchLink>; Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA.; Machine Learning Team, National Institute of Mental Health, Bethesda, MD, USA.<br /><searchLink fieldCode="AU" term="%22Moraczewski+D%22">Moraczewski D</searchLink>; Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA.<br /><searchLink fieldCode="AU" term="%22Earl+E%22">Earl E</searchLink>; Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA.<br /><searchLink fieldCode="AU" term="%22Nielson+DM%22">Nielson DM</searchLink>; Machine Learning Team, National Institute of Mental Health, Bethesda, MD, USA.<br /><searchLink fieldCode="AU" term="%22Loewinger+G%22">Loewinger G</searchLink>; Machine Learning Team, National Institute of Mental Health, Bethesda, MD, USA.<br /><searchLink fieldCode="AU" term="%22McClure+P%22">McClure P</searchLink>; Naval Postgraduate School, Monterey, CA, USA.<br /><searchLink fieldCode="AU" term="%22Thomas+AG%22">Thomas AG</searchLink>; Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA.<br /><searchLink fieldCode="AU" term="%22Pereira+F%22">Pereira F</searchLink>; Machine Learning Team, National Institute of Mental Health, Bethesda, MD, USA.
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  Data: <searchLink fieldCode="JN" term="%22101759493%22">ArXiv</searchLink> [ArXiv] 2024 May 01. <i>Date of Electronic Publication: </i>2024 May 01.
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  Data: <i>Country of Publication: </i>United States <i>NLM ID: </i>101759493 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2331-8422 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2223318422%22">23318422 </searchLink><i>NLM ISO Abbreviation: </i>ArXiv <i>Subsets: </i>PubMed not MEDLINE
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              Text: 2024 May 01
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