The genetic dissection of major depressive disorder (MDD) ranks as one of the success
stories of psychiatric genetics, with genome-wide association studies (GWAS) identifying …

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 …

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 Purpose of Review Artificial intelligence (AI) technology holds both great promise to
transform mental healthcare and potential pitfalls. This article provides an overview of AI and …

It is widely hoped that statistical models can improve decision-making related to medical
treatments. Because of the cost and scarcity of medical outcomes data, this hope is typically …

Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …

Artificial intelligence (AI) is increasingly employed in health care fields such as oncology,
radiology, and dermatology. However, the use of AI in mental health care and …

Depression is widely acknowledged to be a heterogeneous entity, and the need to further
characterize the individual patient who has received this diagnosis in order to personalize …

Mental health researchers and clinicians have long sought answers to the question “What
works for whom?” The goal of precision medicine is to provide evidence-based answers to …

Depression is a heterogeneous and etiologically complex psychiatric syndrome, not a
unitary disease entity, encompassing a broad spectrum of psychopathology arising from …