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...

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Detalles Bibliográficos
Autores principales: Hotzy, Florian, Theodoridou, Anastasia, Hoff, Paul, Schneeberger, Andres R., Seifritz, Erich, Olbrich, Sebastian, Jäger, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Psychiatry
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

Internet

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

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