Artificial Intelligence and Posttraumatic Stress Disorder (PTSD)

Abstract

Abstract. Posttraumatic stress disorder (PTSD) is a debilitating disease that can occur after experiencing a traumatic event. Despite recent progress in computational research, it has not yet been possible to identify precise and reliable risk factors that enable predictive models of individual risk for posttraumatic stress after trauma. In this overview, we discuss recent advances in the use of Machine Learning (ML) and Artificial Intelligence (AI) for risk stratification and targeted treatment allocation in the context of stress pathologies and we critically review the benefits and challenges of emerging approaches. The vast heterogeneity in the manifestation and the etiology of PTSD is discussed as one major reason for the need to deploy ML-based computational models to better account for individual differences between patients. Striving for personalized medicine is one of the most important goals of current clinical research and is of great potential for the field of posttraumatic stress research. The use of ML is a promising and necessary approach for reaching more personalized treatments and to make further progress in the field of precision psychiatry.