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Authors: Maria Cruz 1 and Jorge Bernardino 2

Affiliations: 1 Polytechnic of Coimbra – ISEC, Rua Pedro Nunes, Quinta da Nora, 3030-199 Coimbra and Portugal ; 2 Polytechnic of Coimbra – ISEC, Rua Pedro Nunes, Quinta da Nora, 3030-199 Coimbra, Portugal, CISUC – Centre of Informatics and Systems of University of Coimbra, Pinhal de Marrocos, 3030-290 Coimbra and Portugal

Keyword(s): Data Mining, Cancer, Breast Cancer, Biomarkers, Ensemble.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Computational Intelligence ; Data Analytics ; Data Engineering ; Evolutionary Computing ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: Nowadays, millions of people around the world are living with the diagnosis of cancer, so it is very important to investigate some forms of detection and prevention of this disease. In this paper, we will use an ensemble technique with some data mining algorithms applied to a dataset related to the diagnosis of breast cancer using biological markers found in routine blood tests, in order to diagnose this disease. From the results obtained, it can be verified that the model got an AUC of 95% and a precision of 87%. Thus, through this model it is possible to create new screening tools to assist doctors and prevent healthy patients from having to undergo invasive examinations.

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Paper citation in several formats:
Cruz, M. and Bernardino, J. (2019). Data Mining Techniques for Early Detection of Breast Cancer. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR, ISBN 978-989-758-382-7; ISSN 2184-3228, pages 434-441. DOI: 10.5220/0008346504340441

@conference{kdir19,
author={Maria Cruz. and Jorge Bernardino.},
title={Data Mining Techniques for Early Detection of Breast Cancer},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR,},
year={2019},
pages={434-441},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008346504340441},
isbn={978-989-758-382-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR,
TI - Data Mining Techniques for Early Detection of Breast Cancer
SN - 978-989-758-382-7
IS - 2184-3228
AU - Cruz, M.
AU - Bernardino, J.
PY - 2019
SP - 434
EP - 441
DO - 10.5220/0008346504340441

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