Currently, choice of treatment for mental disorders is determined by trial and error using a “one-size-fits-all” approach resulting in an unacceptably large proportion of non-responding patients. Previous research has been hampered by a focus on single exposures and single outcomes, not accounting for the complexity of mental disorders, hence not leveraging the wealth of data and novel data analytical approaches now available (computer-intensive methods accounting for non-linear relationships and patterns between risk factors and outcomes). Prof. Benros will during this talk discuss advances of artificial intelligence and machine learning in mental health and how Precision Psychiatry can increase the understanding of biological and behavioral mechanisms of mental disorders, and pave the way for more precise diagnostics, prevention and new treatment strategies.