Improving the Instance Selection Method for Better Detection of Depression in Children and Adolescents

Ariane B. da Silva, Maycoln Teodoro, Cristiane Nobre

2024

Abstract

Depression is the leading global cause of disability and often begins in adolescence, a critical period for developing depressive symptoms. Major depressive disorder in the early stages of life is common worldwide but challenging to diagnose. Identifying the most striking profiles of depression in children and adolescents could benefit the training and performance of Machine Learning models and thus help in the diagnosis. Instance Selection is one of the most applied methods for data reduction, allowing the most significant samples to represent them. This work seeks to improve the SI with the Ant Colony Optimization heuristic, introducing stochasticity control to better characterize profiles of children and adolescents with depression. The proposed technique increased the detection rate of individuals with high symptoms in all evaluated algorithms between 0.07 and 8.93 percentage points.

Paper Citation

in Harvard Style

B. da Silva A., Teodoro M. and Nobre C. (2024). Improving the Instance Selection Method for Better Detection of Depression in Children and Adolescents. 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 404-411. DOI: 10.5220/0012355600003657

in Bibtex Style

@conference{healthinf24,
author={Ariane B. da Silva and Maycoln Teodoro and Cristiane Nobre},
title={Improving the Instance Selection Method for Better Detection of Depression in Children and Adolescents},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={404-411},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012355600003657},
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 - Improving the Instance Selection Method for Better Detection of Depression in Children and Adolescents
SN - 978-989-758-688-0
AU - B. da Silva A.
AU - Teodoro M.
AU - Nobre C.
PY - 2024
SP - 404
EP - 411
DO - 10.5220/0012355600003657
PB - SciTePress