ReviewNPJ digital medicine2024
The application of machine learning techniques in posttraumatic stress disorder: a systematic review and meta-analysis.
Review in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning in the prediction of treatment response for emotional disorders: A systematic review and meta-analysis.Clinical psychology review · 2025Pooled it
- Predicting longitudinal post-traumatic stress disorder symptoms using psychological measures and heart rate variability: a machine-learning approach.European journal of psychotraumatology · 2026Article
- Associations Between Childhood Trauma and Personality Functioning and Maladaptive Personality Trait Domains in South Korea: An Alternative DSM-5 Model Approach.Personality and mental health · 2026Article
- Machine learning models for early mortality prediction in trauma patients using public data: a nationwide retrospective study.World journal of emergency surgery : WJES · 2026Article
- Language-based detection of depression with machine learning: systematic review and meta-analysis.NPJ digital medicine · 2026Article
- When does machine learning outperform clinicians? A comparison of prediction accuracy for PTSD treatment outcomes.Psychological medicine · 2025Article
- Can machine learning predict PTSD symptoms from trauma narratives of children and adolescents?European journal of psychotraumatology · 2025Article
- PTSD course and predictors in a 15 year longitudinal cohort following suspected serious injury.Npj mental health research · 2025Article
- Validated metabolomic biomarkers in psychiatric disorders: a narrative review.Molecular medicine (Cambridge, Mass.) · 2025Review
- ECG Signal Analysis for Detection and Diagnosis of Post-Traumatic Stress Disorder: Leveraging Deep Learning and Machine Learning Techniques.Diagnostics (Basel, Switzerland) · 2025Article
- From lab to real-life: A three-stage validation of wearable technology for stress monitoring.MethodsX · 2025Article
- Assessment of PTSD in military personnel via machine learning based on physiological habituation in a virtual immersive environment.Scientific reports · 2025Article
- The role of attachment styles in post-traumatic stress disorder and posttraumatic growth in the Shidu parents of China.SAGE open medicine · 2025Article
- Potential Mitochondria-Related Key Genes in Post-Traumatic Stress Disorder Analyzed by Machine Learning Methods.Neuropsychiatric disease and treatment · 2025Article
- Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis.Behavioral sciences (Basel, Switzerland) · 2024Review
- Predicting the Risk of Loneliness in Children and Adolescents: A Machine Learning Study.Behavioral sciences (Basel, Switzerland) · 2024Article
- Automatic screening for posttraumatic stress disorder in early adolescents following the Ya'an earthquake using text mining techniques.Frontiers in psychiatry · 2024Article
- Artificial intelligence in psychiatry: A systematic review and meta-analysis of diagnostic and therapeutic efficacy.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Posttraumatic stress disorder (PTSD) recently becomes one of the most important mental health concerns. However, no previous study has comprehensively reviewed the application of big data and machine learning (ML) techniques in PTSD. We found 873 studies meet the inclusion criteria and a total of 31 of those in a sample of 210,001 were included in quantitative analysis. ML algorithms were able to discriminate PTSD with an overall accuracy of 0.89. Pooled estimates of classification accuracy from multi-dimensional data (0.96) are higher than single data types (0.86 to 0.90). ML techniques can effectively classify PTSD and models using multi-dimensional data perform better than those using single data types. While selecting optimal combinations of data types and ML algorithms to be clinically applied at the individual level still remains a big challenge, these findings provide insights into the classification, identification, diagnosis and treatment of PTSD.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.