Can we predict who will benefit from cognitive-behavioural therapy? A systematic review and meta-analysis of machine learning studies

The promise of machine learning in predicting treatment outcomes in psychiatry

(2021) Adam M. Chekroud et al.   World Psychiatry

Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis

(2021) Sem E. Cohen et al.   Translational Psychiatry

Toward Generalizable and Transdiagnostic Tools for Psychosis Prediction: An Independent Validation and Improvement of the NAPLS-2 Risk Calculator in the Multisite PRONIA Cohort

(2021) Nikolaos Koutsouleris et al.   BIOLOGICAL PSYCHIATRY

Towards clinical application of prediction models for transition to psychosis: A systematic review and external validation study in the PRONIA sample

(2021) Marlene Rosen et al.   NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

Exploring machine learning to predict depressive relapses of bipolar disorder patients

(2021) Luisa de Siqueira Rotenberg et al.   JOURNAL OF AFFECTIVE DISORDERS

Predicting Alcohol Dependence Treatment Outcomes: A Prospective Comparative Study of Clinical Psychologists vs ‘Trained’ Machine Learning Models

(2020) Martyn Symons et al.   ADDICTION

Predictors of remission from body dysmorphic disorder after internet-delivered cognitive behavior therapy: a machine learning approach

(2020) Oskar Flygare et al.   BMC Psychiatry

FMRI hemodynamic response function (HRF) as a novel marker of brain function: applications for understanding obsessive-compulsive disorder pathology and treatment response

(2020) D. Rangaprakash et al.   Brain Imaging and Behavior

Prediction, Not Association, Paves the Road to Precision Medicine

(2020) Danilo Bzdok et al.   JAMA Psychiatry

Developing a data-driven algorithm for guiding selection between cognitive behavioral therapy, fluoxetine, and combination treatment for adolescent depression

(2020) Meredith Gunlicks-Stoessel et al.   Translational Psychiatry

Comparison of Multivariable Logistic Regression and Other Machine Learning Algorithms for Prognostic Prediction Studies in Pregnancy Care: Systematic Review and Meta-Analysis

(2020) Herdiantri Sufriyana et al.   JMIR Medical Informatics

PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration

(2019) Karel G.M. Moons et al.   ANNALS OF INTERNAL MEDICINE

The trim-and-fill method for publication bias

(2019) Linyu Shi et al.   MEDICINE

Practical recommendations to conduct a neuroimaging meta‐analysis for neuropsychiatric disorders

(2019) Masoud Tahmasian et al.   HUMAN BRAIN MAPPING

Neuroimaging, genetic, clinical, and demographic predictors of treatment response in patients with social anxiety disorder

(2019) Andreas Frick et al.   JOURNAL OF AFFECTIVE DISORDERS

Individual prediction of psychotherapy outcome in posttraumatic stress disorder using neuroimaging data

(2019) Paul Zhutovsky et al.   Translational Psychiatry

Machine Learning Approaches for Clinical Psychology and Psychiatry

(2018) Dominic B. Dwyer et al.   Annual Review of Clinical Psychology

Treatment Selection in Depression

(2018) Zachary D. Cohen et al.   Annual Review of Clinical Psychology

Cognitive behavioral therapy for anxiety and related disorders: A meta-analysis of randomized placebo-controlled trials

(2018) Joseph K. Carpenter et al.   DEPRESSION AND ANXIETY

Multivariate resting-state functional connectivity predicts response to cognitive behavioral therapy in obsessive–compulsive disorder

(2018) Nicco Reggente et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review

(2018) Yena Lee et al.   JOURNAL OF AFFECTIVE DISORDERS

A Machine-Learning Approach to Predicting Smoking Cessation Treatment Outcomes

(2018) Lara N Coughlin et al.   NICOTINE & TOBACCO RESEARCH

The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review

(2018) Taylor A. Burke et al.   JOURNAL OF AFFECTIVE DISORDERS

Prediction of outcome in internet-delivered cognitive behaviour therapy for paediatric obsessive-compulsive disorder: A machine learning approach

(2017) Fabian Lenhard et al.   INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH

Building better biomarkers: brain models in translational neuroimaging

(2017) Choong-Wan Woo et al.   NATURE NEUROSCIENCE

Cross-validation failure: Small sample sizes lead to large error bars

(2017) Gaël Varoquaux   NEUROIMAGE

Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines

(2017) Gaël Varoquaux et al.   NEUROIMAGE

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls

(2017) Mohammad R. Arbabshirani et al.   NEUROIMAGE

Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications

(2017) Sandra Vieira et al.   NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

Prediction of transition to psychosis in patients with a clinical high risk for psychosis: a systematic review of methodology and reporting

(2017) E. Studerus et al.   PSYCHOLOGICAL MEDICINE

What proportion of patients with psychosis is willing to take part in research? A mental health electronic case register analysis

(2017) Rashmi Patel et al.   BMJ Open

Understanding Heterogeneity in Clinical Cohorts Using Normative Models: Beyond Case-Control Studies

(2016) Andre F. Marquand et al.   BIOLOGICAL PSYCHIATRY

Abandoning personalization to get to precision in the pharmacotherapy of depression

(2016) Roy H. Perlis   World Psychiatry

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration

(2015) Karel G.M. Moons et al.   ANNALS OF INTERNAL MEDICINE

The heterogeneity statistic I2 can be biased in small meta-analyses

(2015) Paul T von Hippel   BMC Medical Research Methodology

Brain connectomics predict response to treatment in social anxiety disorder

(2015) S Whitfield-Gabrieli et al.   MOLECULAR PSYCHIATRY

Detecting Neuroimaging Biomarkers for Schizophrenia: A Meta-Analysis of Multivariate Pattern Recognition Studies

(2015) Joseph Kambeitz et al.   NEUROPSYCHOPHARMACOLOGY

From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics

(2015) Thomas Wolfers et al.   NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

Predicting Treatment Response to Cognitive Behavioral Therapy in Panic Disorder With Agoraphobia by Integrating Local Neural Information

(2015) Tim Hahn et al.   JAMA Psychiatry

Predicting long-term outcome of Internet-delivered cognitive behavior therapy for social anxiety disorder using fMRI and support vector machine learning

(2015) K N T Månsson et al.   Translational Psychiatry

Conducting Meta-Analyses inRwith themetaforPackage

(2015) Wolfgang Viechtbauer   Journal of Statistical Software

Who stays, who benefits? Predicting dropout and change in cognitive behaviour therapy for psychosis

(2014) Tania M. Lincoln et al.   PSYCHIATRY RESEARCH

Understanding Sources of Bias in Diagnostic Accuracy Studies

(2013) Robert L. Schmidt et al.   ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE

Single-Subject Anxiety Treatment Outcome Prediction using Functional Neuroimaging

(2013) Tali M Ball et al.   NEUROPSYCHOPHARMACOLOGY

Predictors and Moderators of Internet- and Group-Based Cognitive Behaviour Therapy for Panic Disorder

(2013) Samir El Alaoui et al.   PLoS One

Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research

(2013) Ewout W. Steyerberg et al.   PLOS MEDICINE

Classification of schizophrenia patients and healthy controls from structural MRI scans in two large independent samples

(2012) Mireille Nieuwenhuis et al.   NEUROIMAGE

Patients' beliefs about the causes, persistence and control of psychotic experiences predict take-up of effective cognitive behaviour therapy for psychosis

(2012) D. Freeman et al.   PSYCHOLOGICAL MEDICINE

Implementation of psychological therapies for anxiety and depression in routine practice: Two year prospective cohort study

(2011) David A. Richards et al.   JOURNAL OF AFFECTIVE DISORDERS

Effective elements of cognitive behaviour therapy for psychosis: results of a novel type of subgroup analysis based on principal stratification

(2011) G. Dunn et al.   PSYCHOLOGICAL MEDICINE

To Explain or to Predict?

(2011) Galit Shmueli   STATISTICAL SCIENCE

Neural correlates of sad faces predict clinical remission to cognitive behavioural therapy in depression

(2009) Sergi G. Costafreda et al.   NEUROREPORT

CHoice of Outcome In Cbt for psychosEs (CHOICE): The Development of a New Service User–Led Outcome Measure of CBT for Psychosis

(2009) Kathryn E. Greenwood et al.   SCHIZOPHRENIA BULLETIN