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Machine Learning: An Approach in Identifying Risk Factors for Coercion Compared to Binary Logistic Regression
Introduction: Although knowledge about negative effects of coercive measures in psychiatry exists, its prevalence is still high in clinical routine. This study aimed at define risk factors and test machine learning algorithms for their accuracy in the prediction of the risk to being subjected to coe...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005877/ https://www.ncbi.nlm.nih.gov/pubmed/29946273 http://dx.doi.org/10.3389/fpsyt.2018.00258 |