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Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/6554
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dc.contributor.authorBharat, Chriannaen_US
dc.contributor.authorGlantz, Meyer Den_US
dc.contributor.authorAguilar-Gaxiola, Sergioen_US
dc.contributor.authorAlonso, Jordien_US
dc.contributor.authorBruffaerts, Ronnyen_US
dc.contributor.authorBunting, Brendanen_US
dc.contributor.authorCaldas-de-Almeida, José Miguelen_US
dc.contributor.authorCardoso, Graçaen_US
dc.contributor.authorChardoul, Stephanieen_US
dc.contributor.authorde Jonge, Peteren_US
dc.contributor.authorGureje, Oyeen_US
dc.contributor.authorHaro, Josep Mariaen_US
dc.contributor.authorHarris, Meredith Gen_US
dc.contributor.authorKaram, Elie G.en_US
dc.contributor.authorKawakami, Noritoen_US
dc.contributor.authorKiejna, Andrzejen_US
dc.contributor.authorKovess-Masfety, Vivianeen_US
dc.contributor.authorLee, Singen_US
dc.contributor.authorMcGrath, John Jen_US
dc.contributor.authorMoskalewicz, Jaceken_US
dc.contributor.authorNavarro-Mateu, Fernandoen_US
dc.contributor.authorRapsey, Charleneen_US
dc.contributor.authorSampson, Nancy Aen_US
dc.contributor.authorScott, Kate Men_US
dc.contributor.authorTachimori, Hisateruen_US
dc.contributor.authorTen Have, Margreeten_US
dc.contributor.authorVilagut, Gemmaen_US
dc.contributor.authorWojtyniak, Bogdanen_US
dc.contributor.authorXavier, Miguelen_US
dc.contributor.authorKessler, Ronald Cen_US
dc.contributor.authorDegenhardt, Louisaen_US
dc.date.accessioned2023-02-13T09:03:50Z-
dc.date.available2023-02-13T09:03:50Z-
dc.date.issued2023-05-
dc.identifier.issn09652140-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/6554-
dc.description.abstractLikelihood of alcohol dependence (AD) is increased among people who transition to greater levels of alcohol involvement at a younger age. Indicated interventions delivered early may be effective in reducing risk, but could be costly. One way to increase cost-effectiveness would be to develop a prediction model that targeted interventions to the subset of youth with early alcohol use who are at highest risk of subsequent AD.en_US
dc.language.isoengen_US
dc.publisherWiley Online Libraryen_US
dc.subjectAdolescenceen_US
dc.subjectAlcohol useen_US
dc.subjectCalibrationen_US
dc.subjectDependenceen_US
dc.subjectDiscriminationen_US
dc.subjectMachine learningen_US
dc.titleDevelopment and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol useen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.1111/add.16122-
dc.identifier.pmid36609992-
dc.identifier.scopus2-s2.0-85147387102-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85147387102-
dc.contributor.affiliationFaculty of Medicineen_US
dc.date.catalogued2023-02-13-
dc.description.statusIn Pressen_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=https://doi.org/10.1111/add.16122en_US
dc.relation.ispartoftextAddictionen_US
dc.description.campusSGH campusen_US
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