Comparison between clinician and machine learning prediction in a randomized controlled trial for nonsuicidal self-injury.
Journal:
BMC psychiatry
PMID:
39695442
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 proposed as techniques that might outperform clinicians' judgment. The aim of this study was to explore clinician predictions of which adolescents would abstain from nonsuicidal self-injury after treatment as well as how these predictions match machine-learning algorithm predictions.