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This is a Quantitative Study study (also classified as: Mixed-Methods, Experimental Study).

September 28, 2025Frontiers in PsychiatryOpen Access

Editorial: Women in psychiatry 2024: computational psychiatry

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Editorial highlights gender disparities and equity in computational psychiatry, showcasing machine learning applications in mental health studies.

Gender disparities in psychiatry research persist, with women's authorship at 62% among contributors to the editorial.
Computational methods demonstrated promise in predicting cognitive impairment and understanding psychological conditions.
Diverse machine learning approaches, including Random Forest models, effectively improved accuracy in bipolar disorder predictions.
The development of experimental toolkits for investigating therapeutic alliances shows significant potential for advancing clinical applications.

Zhang et al. (2025) studied this question.

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Editorial highlights gender disparities and equity in computational psychiatry, showcasing machine learning applications in mental health studies.