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),...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Original Paper
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

Internet

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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