Background The clinical high‐risk state for psychosis (CHR‐P) paradigm has facilitated the
implementation of psychosis prevention into clinical practice; however, advancements in …

Background: Artificial intelligence (AI) is giving rise to a revolution in medicine and health
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …

Background: Artificial intelligence (AI) is no longer a futuristic concept; it is increasingly
being integrated into health care. As studies on attitudes toward AI have primarily focused …

Brain age prediction based on imaging data and machine learning (ML) methods has great
potential to provide insights into the development of cognition and mental disorders. Though …

Over the past decade, there has been an abundance of research on the difference between
age and age predicted using brain features, which is commonly referred to as the “brain age …

Schizophrenia is a severe psychiatric disorder associated with both structural and functional
brain abnormalities. In the past few years, there has been growing interest in the application …

This report presents an overview of how machine learning is rapidly advancing clinical
translational imaging in ways that will aid in the early detection, prediction, and treatment of …

Measuring differences between an individual's age and biological age with biological
information from the brain have the potential to provide biomarkers of clinically relevant …

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages,
including high schizotypy, to early and chronic psychosis. However, a comprehensive …

Evidence suggests that psychopathology is associated with an advanced brain ageing
process, typically mapped using machine learning models that predict an individual's age …