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Authors: Juan L. Domínguez-Olmedo 1 ; Jacinto Mata 1 ; Victoria Pachón 1 and Jose L. Lopez-Guerra 2

Affiliations: 1 University of Huelva, Spain ; 2 University Hospital Virgen del Rocío, Spain

Keyword(s): Imbalanced Data Classification, Rules Discovery, Prostate Cancer.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Knowledge-Based Systems ; Pattern Recognition and Machine Learning ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

Abstract: This paper describes a rule-based classifier (DEQAR-C), which is set up by the combination of selected rules after a two-phase process. In the first phase, the rules are generated and sorted for each class, and then a selection is performed to obtain a final list of rules. A real imbalanced dataset regarding the toxicity during and after radiation therapy for prostate cancer has been employed in a comparison with other predictive methods (rule-based, artificial neural networks, trees, Bayesian and logistic regression). DEQAR-C produced excellent results in an evaluation regarding several performance measures (accuracy, Matthews correlation coefficient, sensitivity, specificity, precision, recall and F-measure) and by using cross-validation. Therefore, it was employed to obtain a predictive model using the full data. The resultant model is easily interpretable, combining three rules with two variables, and suggesting conditions that are mostly confirmed by the medical literature.

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Paper citation in several formats:
Domínguez-Olmedo, J.; Mata, J.; Pachón, V. and Lopez-Guerra, J. (2018). A Rule-based Method Applied to the Imbalanced Classification of Radiation Toxicity. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - HEALTHINF; ISBN 978-989-758-281-3; ISSN 2184-4305, SciTePress, pages 147-155. DOI: 10.5220/0006586401470155

@conference{healthinf18,
author={Juan L. Domínguez{-}Olmedo. and Jacinto Mata. and Victoria Pachón. and Jose L. Lopez{-}Guerra.},
title={A Rule-based Method Applied to the Imbalanced Classification of Radiation Toxicity},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - HEALTHINF},
year={2018},
pages={147-155},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006586401470155},
isbn={978-989-758-281-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - HEALTHINF
TI - A Rule-based Method Applied to the Imbalanced Classification of Radiation Toxicity
SN - 978-989-758-281-3
IS - 2184-4305
AU - Domínguez-Olmedo, J.
AU - Mata, J.
AU - Pachón, V.
AU - Lopez-Guerra, J.
PY - 2018
SP - 147
EP - 155
DO - 10.5220/0006586401470155
PB - SciTePress