Overview of Research on Machine Learning in Mental Health: A Brief Scoping Analysis

• Thalles Paul Leandro Mota UFMT
• Claudia Aparecida Martins UFMT
• Leonardo Arruda Vilela Garcia UFMT

DOI: https://doi.org/10.5753/ersimt.2025.8009

Abstract

This scoping study investigates the use of Machine Learning (ML) in Mental Health research using questionnaire data (2020-2024). Analyzing 28 articles from ACM and PubMed, the study reveals a growing trend in research and publications, prevalent use of Random Forest, and a focus on depression. A dichotomy in methodological approaches was observed: Computer Science researchers prioritize comparing algorithm performance, while Health researchers favor applying more interpretable models. ML application in Mental Health shows significant potential as a supplementary tool for professionals.

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