This paper is in the following e-collection/theme issue:

Intentional Self-Harm (89) Machine Learning (1373) Bipolar Disorders (55) Depression and Mood Disorders; Suicide Prevention (1273)

Published on in Vol 8, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24522, first published .
Using Machine Learning Imputed Outcomes to Assess Drug-Dependent Risk of Self-Harm in Patients with Bipolar Disorder: A Comparative Effectiveness Study

Using Machine Learning Imputed Outcomes to Assess Drug-Dependent Risk of Self-Harm in Patients with Bipolar Disorder: A Comparative Effectiveness Study

Using Machine Learning Imputed Outcomes to Assess Drug-Dependent Risk of Self-Harm in Patients with Bipolar Disorder: A Comparative Effectiveness Study

Authors of this article:

Anastasiya Nestsiarovich1 Author Orcid Image ;   Praveen Kumar2 Author Orcid Image ;   Nicolas Raymond Lauve2 Author Orcid Image ;   Nathaniel G Hurwitz3 ;   Aurélien J Mazurie4 Author Orcid Image ;   Daniel C Cannon5 Author Orcid Image ;   Yiliang Zhu6 Author Orcid Image ;   Stuart James Nelson7 Author Orcid Image ;   Annette S Crisanti8 Author Orcid Image ;   Berit Kerner9 Author Orcid Image ;   Mauricio Tohen8 Author Orcid Image ;   Douglas J Perkins1 Author Orcid Image ;   Christophe Gerard Lambert1, 10 Author Orcid Image
Article Authors Cited by (3) Tweetations (10) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.