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The application of machine learning techniques in posttraumatic stress disorder: a systematic review and meta-analysis.
- Source :
- NPJ Digital Medicine; 5/9/2024, Vol. 7 Issue 1, p1-13, 13p
- Publication Year :
- 2024
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- TREATMENT of post-traumatic stress disorder
DIAGNOSIS of post-traumatic stress disorder
POST-traumatic stress disorder
MEDICAL information storage & retrieval systems
META-analysis
DESCRIPTIVE statistics
SYSTEMATIC reviews
MEDLINE
MEDICAL databases
MACHINE learning
ONLINE information services
DATA analysis software
ALGORITHMS
PSYCHOLOGY information storage & retrieval systems
Subjects
Details
- Language :
- English
- ISSN :
- 23986352
- Volume :
- 7
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- NPJ Digital Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 177194523
- Full Text :
- https://doi.org/10.1038/s41746-024-01117-5