Background: Psychiatric disorders have been historically classified using symptom
information alone. Recently, there has been a dramatic increase in research interest not only …

Traditional psychiatric diagnosis has been overly reliant on either self-reported measures
(introspection) or clinical rating scales (interviews). This produced the so-called explanatory …

Much attention is currently devoted to developing diagnostic classifiers for mental disorders.
Complementing these efforts, we highlight the potential of machine learning to gain …

Objective Diagnoses using imaging-based measures alone offer the hope of improving the
accuracy of clinical diagnosis, thereby reducing the costs associated with incorrect …

The advent of functional imaging has led to a new wave of insights into the pathophysiology
and treatment of psychiatric disorders. In this Perspective, schizophrenia is used as an …

Precision functional mapping (PFM) is a neuroimaging approach to reliably estimate metrics
of brain function from individual people via the collection of large amounts of fMRI data …

Psychiatric disorders are complex, involving heterogeneous symptomatology and
neurobiology that rarely involves the disruption of single, isolated brain structures. In an …

Functional neuroimaging emerged with great promise and has provided fundamental
insights into the neurobiology of schizophrenia. However, it has faced challenges and …

Mood disorders are a highly prevalent group of mental disorders causing substantial
socioeconomic burden. There are various methodological approaches for identifying the …

Importance Psychiatric diagnoses are currently distinguished based on sets of specific
symptoms. However, genetic and clinical analyses find similarities across a wide variety of …