Comparison between clinician and machine learning prediction in a randomized controlled trial for nonsuicidal self-injury

Comparison between clinician and machine learning prediction in a randomized controlled trial for nonsuicidal self-injury

Abstract Background Nonsuicidal self-injury is a common health problem in adolescents and associated with future suicidal behavior. Predicting who will benefit from treatment is an urgent and a critical first step towards personalized treatment approaches. Machine-learning algorithms have been propo...

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Bibliographic Details
Main Authors: Moa Pontén, Oskar Flygare, Martin Bellander, Moa Karemyr, Jannike Nilbrink, Clara Hellner, Olivia Ojala, Johan Bjureberg
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Psychiatry
Subjects:
Artificial intelligence
Random forest analysis
Nonsuicidal self-injury
Emotion regulation
Machine learning
Online Access:https://doi.org/10.1186/s12888-024-06391-x
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https://doi.org/10.1186/s12888-024-06391-x

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