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Using neuroimaging to predict relapse in stimulant dependence: A comparison of linear and machine learning models
OBJECTIVE: Relapse rates are consistently high for stimulant user disorders. In order to obtain prognostic information about individuals in treatment, machine learning models have been applied to neuroimaging and clinical data. Yet few efforts have been made to test these models in independent sampl...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350259/ https://www.ncbi.nlm.nih.gov/pubmed/30665102 http://dx.doi.org/10.1016/j.nicl.2019.101676 |