An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis
Rawls and colleagues use an advanced statistical approach to identify causal neurobehavioral mechanisms underlying Alcohol Use Disorder. Their findings support current multifactorial models of addiction, but also highlight the importance of social factors in addiction maintenance.
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2021-03-01
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Series: | Communications Biology |
Online Access: | https://doi.org/10.1038/s42003-021-01955-z |
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doaj-6f07ae07a7674b24a0447204712add142021-04-04T11:27:32ZengNature Publishing GroupCommunications Biology2399-36422021-03-014111210.1038/s42003-021-01955-zAn integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysisEric Rawls0Erich Kummerfeld1Anna Zilverstand2Department of Psychiatry and Behavioral Sciences, University of MinnesotaInstitute for Health Informatics, University of MinnesotaDepartment of Psychiatry and Behavioral Sciences, University of MinnesotaRawls and colleagues use an advanced statistical approach to identify causal neurobehavioral mechanisms underlying Alcohol Use Disorder. Their findings support current multifactorial models of addiction, but also highlight the importance of social factors in addiction maintenance.https://doi.org/10.1038/s42003-021-01955-z |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Eric Rawls Erich Kummerfeld Anna Zilverstand |
spellingShingle |
Eric Rawls Erich Kummerfeld Anna Zilverstand An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis Communications Biology |
author_facet |
Eric Rawls Erich Kummerfeld Anna Zilverstand |
author_sort |
Eric Rawls |
title |
An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_short |
An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_full |
An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_fullStr |
An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_full_unstemmed |
An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_sort |
integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
publisher |
Nature Publishing Group |
series |
Communications Biology |
issn |
2399-3642 |
publishDate |
2021-03-01 |
description |
Rawls and colleagues use an advanced statistical approach to identify causal neurobehavioral mechanisms underlying Alcohol Use Disorder. Their findings support current multifactorial models of addiction, but also highlight the importance of social factors in addiction maintenance. |
url |
https://doi.org/10.1038/s42003-021-01955-z |
work_keys_str_mv |
AT ericrawls anintegratedmultimodalmodelofalcoholusedisordergeneratedbydatadrivencausaldiscoveryanalysis AT erichkummerfeld anintegratedmultimodalmodelofalcoholusedisordergeneratedbydatadrivencausaldiscoveryanalysis AT annazilverstand anintegratedmultimodalmodelofalcoholusedisordergeneratedbydatadrivencausaldiscoveryanalysis AT ericrawls integratedmultimodalmodelofalcoholusedisordergeneratedbydatadrivencausaldiscoveryanalysis AT erichkummerfeld integratedmultimodalmodelofalcoholusedisordergeneratedbydatadrivencausaldiscoveryanalysis AT annazilverstand integratedmultimodalmodelofalcoholusedisordergeneratedbydatadrivencausaldiscoveryanalysis |
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1721542737465966592 |