Systematic review of machine learning in PTSD studies for automated diagnosis evaluation.

ABSTRACT: Post-traumatic stress disorder (PTSD) is frequently underdiagnosed due to its clinical and biological heterogeneity. Worldwide, many people face barriers to accessing accurate and timely diagnoses. Machine learning (ML) techniques have been utilized for early assessments and outcome prediction to address these challenges. This paper aims to conduct a systematic review to investigate if ML is a promising approach for PTSD diagnosis. In this review, statistical methods were employed to synthesize the outcomes of the included research and provide guidance on critical considerations for ML task implementation. These included (a) selection of the most appropriate ML model for the available dataset, (b) identification of optimal ML features based on the chosen diagnostic method, (c) determinatio

SUBMITTER: Wu Y 

PROVIDER: S-EPMC10955977 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature