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Authors: Ana C. M. Gonçalves ; Ludmila Nascimento ; Ana L. P. Leite ; Maria E. O. Brito ; Erika G. de Assis ; Henrique Freitas and Cristiane Nobre

Affiliation: Department of Computer Science, Pontifical Catholic University of Minas Gerais, Av. Dom José Gaspar, Belo Horizonte, Brazil

Keyword(s): Zika, Ant Colony, Selection Instance, Microcephaly, Congenital Zika Syndrome.

Abstract: This article investigates congenital syndrome associated with the Zika virus (ZIKV) in newborns in Brazil, utilizing preprocessing techniques and machine learning to enhance its detection. The study proposes the Ant Colony Optimization (ACO) algorithm for instance selection in a database on ZIKV infections from 2016, during a period when Brazil faced a Zika outbreak linked to neurological complications such as microcephaly. The research compares the performance of ACO with five classification algorithms, demonstrating that ACO improved all evaluation metrics. The highest case concentration was observed in Brazil’s Northeast and Southeast regions. Although cases have decreased in 2024, it is essential to maintain monitoring and preventive actions. In summary, the results confirm the effectiveness of ACO in enhancing machine learning models and highlight the importance of clinical attributes in the early detection of congenital syndromes, recommending the use of updated databases for a better understanding of the impact of ZIKV, particularly in newborns. (More)

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Paper citation in several formats:
Gonçalves, A. C. M., Nascimento, L., Leite, A. L. P., Brito, M. E. O., G. de Assis, E., Freitas, H. and Nobre, C. (2025). Selection of Representative Instances Using Ant Colony Optimization: A Case Study in a Database of Newborns with Congenital Zika in Brazil. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF; ISBN 978-989-758-731-3; ISSN 2184-4305, SciTePress, pages 587-594. DOI: 10.5220/0013172600003911

@conference{healthinf25,
author={Ana C. M. Gon\c{c}alves and Ludmila Nascimento and Ana L. P. Leite and Maria E. O. Brito and Erika {G. de Assis} and Henrique Freitas and Cristiane Nobre},
title={Selection of Representative Instances Using Ant Colony Optimization: A Case Study in a Database of Newborns with Congenital Zika in Brazil},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF},
year={2025},
pages={587-594},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013172600003911},
isbn={978-989-758-731-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF
TI - Selection of Representative Instances Using Ant Colony Optimization: A Case Study in a Database of Newborns with Congenital Zika in Brazil
SN - 978-989-758-731-3
IS - 2184-4305
AU - Gonçalves, A.
AU - Nascimento, L.
AU - Leite, A.
AU - Brito, M.
AU - G. de Assis, E.
AU - Freitas, H.
AU - Nobre, C.
PY - 2025
SP - 587
EP - 594
DO - 10.5220/0013172600003911
PB - SciTePress

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