![]() One-third of the studies (n=56) did not report any preprocessing or data preparation. Quality assessment revealed important flaws in the process of AI application and data preprocessing pipelines. ![]() Models usually applied a combination of questionnaires and scales to assess symptom severity using electronic health records (n=49) as well as medical images (n=33). AI was typically applied to evaluate quality of treatments (n=44) or stratify patients into subgroups and clusters (n=31). Most interventions were based on randomized controlled trials (n=62), followed by prospective cohorts (n=24) among observational studies. Predominant categories were Depressive disorders (n=70) and Schizophrenia or other primary psychotic disorders (n=26). ![]() ![]() The distribution of AI applications in mental health was found unbalanced between ICD-11 mental health categories. A total of 429 nonduplicated records were retrieved from the databases and 129 were included for a full assessment-18 of which were manually added. ![]()
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