Mental health concerns are common, and various evidence-based interventions for mental
health conditions have been developed. However, many people have difficulty accessing�…

Neuropsychiatric disorders pose a high societal cost, but their treatment is hindered by lack
of objective outcomes and fidelity metrics. AI technologies and specifically Natural�…

For many years, psychiatrists have tried to understand factors involved in response to
medications or psychotherapies, in order to personalize their treatment choices. There is�…

Abstract Machine learning (ML) offers robust statistical and probabilistic techniques that can
help to make sense of large amounts of data. This scoping review paper aims to broadly�…

There is a largeand growing need for mental health services worldwide, but there is a
massive shortage of mental health specialists to meet these needs—particularly�…

In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new�…

Advances in machine learning and contactless sensors have given rise to ambient
intelligence—physical spaces that are sensitive and responsive to the presence of humans�…

Background Innovative technologies, such as machine learning, big data, and artificial
intelligence (AI) are approaches adopted for personalized medicine, and psychological�…

In this conceptual paper, we outline the many challenges on the road to personalized
psychotherapy, using the example of cognitive behavior therapy (CBT) for depression. To�…

Depression is a leading cause of disability worldwide, but is often underdiagnosed and
undertreated. Cognitive behavioural therapy holds that individuals with depression exhibit�…