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Using Machine Learning Imputed Outcomes to Assess Drug-Dependent Risk of Self-Harm in Patients with Bipolar Disorder: A Comparative Effectiveness Study
BACKGROUND: Incomplete suicidality coding in administrative claims data is a known obstacle for observational studies. With most of the negative outcomes missing from the data, it is challenging to assess the evidence on treatment strategies for the prevention of self-harm in bipolar disorder (BD),...
Autores principales: | Nestsiarovich, Anastasiya, Kumar, Praveen, Lauve, Nicolas Raymond, Hurwitz, Nathaniel G, Mazurie, Aurélien J, Cannon, Daniel C, Zhu, Yiliang, Nelson, Stuart James, Crisanti, Annette S, Kerner, Berit, Tohen, Mauricio, Perkins, Douglas J, Lambert, Christophe Gerard |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100888/ https://www.ncbi.nlm.nih.gov/pubmed/33688834 http://dx.doi.org/10.2196/24522 |
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