Abstract Background Eating Disorders (EDs) are one of the most complex psychiatric
disorders, with significant impairment of psychological and physical health, and …

Objective To provide a brief overview of artificial intelligence (AI) application within the field
of eating disorders (EDs) and propose focused solutions for research. Method An overview …

Abstract Machine learning approaches are just emerging in eating disorders research.
Promising early results suggest that such approaches may be a particularly promising and …

Advances in machine learning and digital data provide vast potential for mental health
predictions. However, research using machine learning in the field of eating disorders is just …

BackgroundPsychiatric disorders, including eating disorders (EDs), have clinical outcomes
that range widely in severity and chronicity. The ability to predict such outcomes is extremely …

Precision Medicine is the term used to encapsulate treatments tailored to the individual
patient on the basis of genetic, biological, phenotypic, or psychosocial factors. It therefore …

BackgroundDespite a wide range of proposed risk factors and theoretical models, prediction
of eating disorder (ED) onset remains poor. This study undertook the first comparison of two …

Abstract Objective Eating disorders (EDs) are serious mental illnesses with high mortality
and relapse rates and carry significant societal and personal costs. Nevertheless, there are …

Eating disorders (EDs) represent a contradictory chapter of clinical psychiatry, ie, although
they are associated with significant prevalence and risks in the long term (including vital risk …

Eating disorders (EDs) are complex mental health conditions that affect millions of
individuals worldwide. We face a future with recent increases in disordered eating pathology …