New and emerging approaches to treat psychiatric disorders

KW Scangos, MW State, AH Miller, JT Baker… - Nature medicine, 2023 - nature.com
Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact
the lives of millions of people worldwide. Although their etiological and diagnostic …

Measurement-based and data-informed psychological therapy

W Lutz, B Schwartz, J Delgadillo - Annual Review of Clinical …, 2022 - annualreviews.org
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 …

The promise of machine learning in predicting treatment outcomes in psychiatry

AM Chekroud, J Bondar, J Delgadillo… - World …, 2021 - Wiley Online Library
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 …

The efficacy and effectiveness of psychological therapies

M Barkham, MJ Lambert - Bergin and Garfield's handbook of …, 2021 - books.google.com
This chapter sets out the current status of the evidence-base for the efficacy and
effectiveness of psychological therapies. First, methods for eliciting and synthesizing …

[HTML][HTML] Methodological and quality flaws in the use of artificial intelligence in mental health research: systematic review

R Tornero-Costa, A Martinez-Millana… - JMIR Mental …, 2023 - mental.jmir.org
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 …

Machine learning and big data in psychiatry: toward clinical applications

RB Rutledge, AM Chekroud, QJM Huys - Current opinion in neurobiology, 2019 - Elsevier
Highlights•The combination of data-driven machine learning and theory-driven
computational models holds great promise for psychiatry.•Machine-learning analyses of …

Sample size requirements for multivariate models to predict between-patient differences in best treatments of major depressive disorder

A Luedtke, E Sadikova… - Clinical Psychological …, 2019 - journals.sagepub.com
Clinical trials have documented numerous clinical features, social characteristics, and
biomarkers that are “prescriptive” predictors of depression treatment response, that is …

Personalized treatment selection in routine care: Integrating machine learning and statistical algorithms to recommend cognitive behavioral or psychodynamic therapy

B Schwartz, ZD Cohen, JA Rubel… - Psychotherapy …, 2021 - Taylor & Francis
Objective: This study aims at developing a treatment selection algorithm using a
combination of machine learning and statistical inference to recommend patients' optimal …

Multi-omics data integration methods and their applications in psychiatric disorders

A Sathyanarayanan, TT Mueller, MA Moni… - European …, 2023 - Elsevier
To study mental illness and health, in the past researchers have often broken down their
complexity into individual subsystems (eg, genomics, transcriptomics, proteomics, clinical …

Personalized treatment approaches.

ZD Cohen, J Delgadillo, RJ DeRubeis - 2021 - psycnet.apa.org
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 …