In this Series paper, we explore the promises and challenges of artificial intelligence (AI)-
based precision medicine tools in mental health care from clinical, ethical, and regulatory …

The high global prevalence of depression, together with the recent acceleration of remote
care owing to the COVID-19 pandemic, has prompted increased interest in the efficacy of …

Cognitive and behavioural flexibility permit the appropriate adjustment of thoughts and
behaviours in response to changing environmental demands. Brain mechanisms enabling …

Abstract Machine learning is increasingly used in mental health research and has the
potential to advance our understanding of how to characterize, predict, and treat mental …

Anxiety is experienced in response to threats that are distal or uncertain, involving changes
in one's subjective state, autonomic responses, and behavior. Defensive and physiologic …

In this chapter, we explore Support Vector Machine (SVM)—a machine learning method that
has become exceedingly popular for neuroimaging analysis in recent years. Because of …

Practitioners frequently use diagnostic criteria to identify children with neurodevelopmental
disorders and to guide intervention decisions. These criteria also provide the organising …

The network approach to psychopathology posits that mental disorders can be
conceptualized and studied as causal systems of mutually reinforcing symptoms. This …

Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake,
behaving human brain. By tracking whole-brain signals across a diverse range of cognitive …

Predictive coding offers a potentially unifying account of cortical function--postulating that the
core function of the brain is to minimize prediction errors with respect to a generative model …