Hybrid PSO-Based Rule Classifier for Disease Detection

Cecilia Mariciuc, Cecilia Mariciuc, Madalina Raschip

2024

Abstract

The application of data mining techniques in healthcare is common because the decision-making process for the diagnosis of medical conditions could benefit from the information extracted. A decision system must not only be accurate but also provide understandable explanations for its reasoning. Rule-based models seek to find a small set of rules that can effectively categorize data while providing great human readability. Rule discovery is a complex optimization problem, making it a good candidate for the application of PSO, a versatile, intuitive search algorithm. In this paper, a particle swarm optimization algorithm is used for learning classification rules as part of a Covering-based rule classifier. The proposed PSO is hybridized with the Iterated Local Search metaheuristic, and association rules are used as part of the initialization step. The classifier is tested on several unbalanced medical disease datasets with different types of attributes to more faithfully reflect real-world data. When compared with state-of-the-art rule-based classifiers, the studied algorithm shows good results and is highly interpretable.

Paper Citation

in Harvard Style

Mariciuc C. and Raschip M. (2024). Hybrid PSO-Based Rule Classifier for Disease Detection. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 906-914. DOI: 10.5220/0012417900003636

in Bibtex Style

@conference{icaart24,
author={Cecilia Mariciuc and Madalina Raschip},
title={Hybrid PSO-Based Rule Classifier for Disease Detection},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={906-914},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012417900003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Hybrid PSO-Based Rule Classifier for Disease Detection
SN - 978-989-758-680-4
AU - Mariciuc C.
AU - Raschip M.
PY - 2024
SP - 906
EP - 914
DO - 10.5220/0012417900003636
PB - SciTePress