Machine Learning Predicts Conduct Disorder in Kids
[Source: Science Daily]
Conduct disorder (CD) is a common yet complex psychiatric disorder featuring aggressive and destructive behavior. Factors contributing to the development of CD span biological, psychological, and social domains. Researchers have identified a myriad of risk factors that could help predict CD, but they are often considered in isolation. Now, a new study uses a machine-learning approach for the first time to assess risk factors across all three domains in combination and predict later development of CD with high accuracy.
The study appears in Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, published by Elsevier.
The researchers used baseline data from over 2,300 children aged 9 to 10 enrolled in the Adolescent Brain Cognitive Development (ABCD) Study, a longitudinal study following the biopsychosocial development of children. The researchers “trained” their machine-learning model using previously identified risk factors from across multiple biopsychosocial domains. For example, measures in
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