New and emerging approaches to treat psychiatric disorders
Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact
the lives of millions of people worldwide. Although their etiological and diagnostic …
the lives of millions of people worldwide. Although their etiological and diagnostic …
Measurement-based and data-informed psychological therapy
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 …
decade. This review discusses key issues related to outcome measurement, modeling, and …
The promise of machine learning in predicting treatment outcomes in psychiatry
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 …
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 …
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 …
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …
Machine learning and big data in psychiatry: toward clinical applications
Highlights•The combination of data-driven machine learning and theory-driven
computational models holds great promise for psychiatry.•Machine-learning analyses of …
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 …
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
Objective: This study aims at developing a treatment selection algorithm using a
combination of machine learning and statistical inference to recommend patients' optimal …
combination of machine learning and statistical inference to recommend patients' optimal …
Multi-omics data integration methods and their applications in psychiatric disorders
To study mental illness and health, in the past researchers have often broken down their
complexity into individual subsystems (eg, genomics, transcriptomics, proteomics, clinical …
complexity into individual subsystems (eg, genomics, transcriptomics, proteomics, clinical …
Personalized treatment approaches.
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 …
optimize treatment for each individual has been an important challenge. For the therapist …