Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact
the lives of millions of people worldwide. Although their etiological and diagnostic …

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 …

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 …

First, methods for eliciting and synthesizing evidence on efficacy and effectiveness are
briefly outlined. We then address questions pertaining to the general and specific efficacy …

Outcome measurement in the field of psychotherapy has developed considerably in the last
decade. This review discusses key issues related to outcome measurement, modeling, and …

Highlights•The combination of data-driven machine learning and theory-driven
computational models holds great promise for psychiatry.•Machine-learning analyses of …

To study mental illness and health, in the past researchers have often broken down their
complexity into individual subsystems (eg, genomics, transcriptomics, proteomics, clinical …

Objective: This study aims at develo** a treatment selection algorithm using a
combination of machine learning and statistical inference to recommend patients' optimal …

In the modern history of psychotherapy, understanding the individual patient and how to
optimize treatment for each individual has been an important challenge. For the therapist …

Large variability in the individual response to even the most-efficacious pain treatments is
observed clinically, which has led to calls for a more personalized, tailored approach to …