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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Principais autores:	Moa Pontén, Oskar Flygare, Martin Bellander, Moa Karemyr, Jannike Nilbrink, Clara Hellner, Olivia Ojala, Johan Bjureberg
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2024-12-01
coleção:	BMC Psychiatry
Assuntos:	Artificial intelligence Random forest analysis Nonsuicidal self-injury Emotion regulation Machine learning
Acesso em linha:	https://doi.org/10.1186/s12888-024-06391-x
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