Using Data Mining Techniques to Understand Patterns of Suicide and Reattempt Rates in Southern Brazil

Caibe Pereira, Rômulo Peixoto, Manuella Kaster, Mateus Grellert, Jônata Carvalho

2024

Abstract

Suicide is a multifactorial, complex condition and one of the leading global causes of death, with suicide attempt as the main risk factor. To this day, studies have shown relevant indicators that help identify people with risk of committing suicide, but the literature still lacks comprehensive studies that evaluate how different risk factors interact and ultimately affects the suicide risk. In this paper, we aimed to identify patterns in data from the Brazilian Unified Health System – SUS, from 2009 to 2020, of individual reports of suicide attempts and suicide deaths in the Brazilian Southern States, integrating those with a database of the healthcare infrastructure. We framed the problem as a classification task for each micro-region to predict suicide and reattempt rate as low, moderate, or high. We developed a pipeline for integrating, cleaning, and selecting the data, and trained and compared three machine learning models: Decision Tree, Random Forest, and XGBoost, with approximately 97% accuracy. The most important features for predicting suicide rates were the number of mental health units and clinics, and for both suicide and reattempts were the number of physicians and nurses available. This novel result brings valuable knowledge on possible directions for governmental investments in order to reduce suicide rates.

Paper Citation

in Harvard Style

Pereira C., Peixoto R., Kaster M., Grellert M. and Carvalho J. (2024). Using Data Mining Techniques to Understand Patterns of Suicide and Reattempt Rates in Southern Brazil. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-688-0, SciTePress, pages 385-392. DOI: 10.5220/0012350500003657

in Bibtex Style

@conference{healthinf24,
author={Caibe Pereira and Rômulo Peixoto and Manuella Kaster and Mateus Grellert and Jônata Carvalho},
title={Using Data Mining Techniques to Understand Patterns of Suicide and Reattempt Rates in Southern Brazil},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={385-392},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012350500003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - Using Data Mining Techniques to Understand Patterns of Suicide and Reattempt Rates in Southern Brazil
SN - 978-989-758-688-0
AU - Pereira C.
AU - Peixoto R.
AU - Kaster M.
AU - Grellert M.
AU - Carvalho J.
PY - 2024
SP - 385
EP - 392
DO - 10.5220/0012350500003657
PB - SciTePress