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This article evaluates the methodological features of machine-learning-based studies on post-traumatic stress disorder (PTSD) and provides insights on important considerations for such studies. The majority of the studies employed rigorous assessment methods and provided comprehensive details on the ML techniques used and performance metrics. Additionally, a significant number of studies utilized independent datasets to assess model performance.
