AI-Driven Early Mental Health Screening: Analyzing Selfies of Pregnant Women

Gustavo A. Basílio, Thiago B. Pereira, Alessandro L. Koerich, Hermano Tavares, Ludmila Dias, Maria G. S. Teixeira, Rafael Sousa, Wilian H. Hisatugu, Amanda S. Mota, Anilton S. Garcia, Marco Aurélio K. Galletta, Thiago M. Paixão

2025

Abstract

Major Depressive Disorder and anxiety disorders affect millions globally, contributing significantly to the burden of mental health issues. Early screening is crucial for effective intervention, as timely identification of mental health issues can significantly improve treatment outcomes. Artificial intelligence (AI) can be valuable for improving the screening of mental disorders, enabling early intervention and better treatment outcomes. AI-driven screening can leverage the analysis of multiple data sources, including facial features in digital images. However, existing methods often rely on controlled environments or specialized equipment, limiting their broad applicability. This study explores the potential of AI models for ubiquitous depression-anxiety screening given face-centric selfies. The investigation focuses on high-risk pregnant patients, a population that is particularly vulnerable to mental health issues. To cope with limited training data resulting from our clinical setup, pre-trained models were utilized in two different approaches: fine-tuning convolutional neural networks (CNNs) originally designed for facial expression recognition and employing vision-language models (VLMs) for zero-shot analysis of facial expressions. Experimental results indicate that the proposed VLM-based method significantly outperforms CNNs, achieving an accuracy of 77.6%. Although there is significant room for improvement, the results suggest that VLMs can be a promising approach for mental health screening.

Paper Citation

in Harvard Style

Basílio G., Pereira T., Koerich A., Tavares H., Dias L., Teixeira M., Sousa R., Hisatugu W., Mota A., Garcia A., Galletta M. and Paixão T. (2025). AI-Driven Early Mental Health Screening: Analyzing Selfies of Pregnant Women. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-731-3, SciTePress, pages 308-318. DOI: 10.5220/0013372100003911

in Bibtex Style

@conference{healthinf25,
author={Gustavo Basílio and Thiago Pereira and Alessandro Koerich and Hermano Tavares and Ludmila Dias and Maria Teixeira and Rafael Sousa and Wilian Hisatugu and Amanda Mota and Anilton Garcia and Marco Galletta and Thiago Paixão},
title={AI-Driven Early Mental Health Screening: Analyzing Selfies of Pregnant Women},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2025},
pages={308-318},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013372100003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - AI-Driven Early Mental Health Screening: Analyzing Selfies of Pregnant Women
SN - 978-989-758-731-3
AU - Basílio G.
AU - Pereira T.
AU - Koerich A.
AU - Tavares H.
AU - Dias L.
AU - Teixeira M.
AU - Sousa R.
AU - Hisatugu W.
AU - Mota A.
AU - Garcia A.
AU - Galletta M.
AU - Paixão T.
PY - 2025
SP - 308
EP - 318
DO - 10.5220/0013372100003911
PB - SciTePress