The limiting step toward effective prevention and early intervention is the ability to timely identify young people who might be at risk of developing a severe mental disorder. The gap between research evidence and clinical practice is still wide due to several important challenges: 1) the typically multi-syndromal or unspecific nature of mental disorders in transitional age (i.e., adolescence) makes it difficult to identify clinical targets and set priorities for intervention. 2) Scalable methods across different levels of stratified risk in the early stages of mental disorders have been implemented in the form of clinical prediction calculators and neuroimaging models that enable early detection of patients at risk for psychotic disorders, individualized diagnosis, prognosis, and treatment planning.
This topic was explored in the form of a symposium entitled AI in prognostic psychiatry. This symposium was held at the 14th International Conference on Early Intervention in Mental Health. It was chaired by Stefan Borgwardt and co-chaired by Paolo Fusar-Poli from King’s College London. Presenters included Christina Andreou (University of Lausanne and University of Lübeck), Dominic Oliver (King’s College London), Alexanandra Korda (University of Lübeck) and Su Lui (Uni Chendgu, China).