Conference Publication – Predicting Adverse Childhood Experiences via Machine Learning Ensembles

Predicting Adverse Childhood Experiences via Machine Learning Ensembles Recently, we collaborated with the Indian Institute of Technology Mandi team to understand if predicting exposure to childhood trauma (Adverse Childhood Experiences-ACEs) is possible without directly asking questions about specific ACEs. We found that by understanding specific internalization experiences (such as well-being, depression and anxiety, sleep quality) and externalizing behaviours (such as suicide behaviour, ability to focus, history of self-harm, etc.), it is possible to understand if the individual has been exposed to low or high ACE level. The findings affect psychotherapists, psychologists and psychiatrists since many people take the time or