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Network-level enrichment provides a framework for biological interpretation of machine learning results.

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Title: Network-level enrichment provides a framework for biological interpretation of machine learning results.
Authors: Li J; Department of Statistics and Data Science, Washington University in St. Louis, MO, USA., Segel A; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA., Feng X; Department of Statistics and Data Science, Washington University in St. Louis, MO, USA., Tu JC; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA., Eck A; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA., King KT; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA., Adeyemo B; Department of Neurology, Washington University in St. Louis, MO, USA., Karcher NR; Department of Psychiatry, Washington University in St. Louis, MO, USA., Chen L; Department of Statistics and Data Science, Washington University in St. Louis, MO, USA., Eggebrecht AT; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA., Wheelock MD; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA.
Source: Network neuroscience (Cambridge, Mass.) [Netw Neurosci] 2024 Oct 01; Vol. 8 (3), pp. 762-790. Date of Electronic Publication: 2024 Oct 01 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: MIT Press Country of Publication: United States NLM ID: 101719149 Publication Model: eCollection Cited Medium: Internet ISSN: 2472-1751 (Electronic) Linking ISSN: 24721751 NLM ISO Abbreviation: Netw Neurosci Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Li+J%22">Li J</searchLink>; Department of Statistics and Data Science, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Segel+A%22">Segel A</searchLink>; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Feng+X%22">Feng X</searchLink>; Department of Statistics and Data Science, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Tu+JC%22">Tu JC</searchLink>; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Eck+A%22">Eck A</searchLink>; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22King+KT%22">King KT</searchLink>; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Adeyemo+B%22">Adeyemo B</searchLink>; Department of Neurology, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Karcher+NR%22">Karcher NR</searchLink>; Department of Psychiatry, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Chen+L%22">Chen L</searchLink>; Department of Statistics and Data Science, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Eggebrecht+AT%22">Eggebrecht AT</searchLink>; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA.<br /><searchLink fieldCode="AU" term="%22Wheelock+MD%22">Wheelock MD</searchLink>; Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22MIT+Press%22">MIT Press </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101719149 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2472-1751 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2224721751%22">24721751 </searchLink><i>NLM ISO Abbreviation: </i>Netw Neurosci <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.1162/netn_a_00383
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              Text: 2024 Oct 01
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