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Authors: Marc Almiñana 1 ; Alejandro Rabasa 1 ; Laureano Santamaría 1 ; Laureano F. Escudero 2 ; Antonio F. Compañ 1 and Agustín Pérez-Martín 1

Affiliations: 1 Universidad Miguel Hernández, Spain ; 2 Universidad Rey Juan Carlos, Spain

ISBN: 978-989-674-016-0

ISSN: 2184-4305

Keyword(s): Data Mining, Forecasting methods, Diagnosis, Breast cancer.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Different methods are usually applied for medical diagnosis problems. Most of them are only based on expert knowledge and the results are provided by model-driven methods and they are built from inflexible mathematical expressions. In this paper we suggest a Data-Driven perspective to facilitate the medical expert labour on diagnosis tasks. Furthermore, this paper offers a step by step procedure to select the most accurate forecasting method depending on the nature of the variables and the structure problem constraints. To validate such a selecting procedure, we apply it to a breast cancer diagnosis problem as a real case study.

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Paper citation in several formats:
Almiñana M.; Rabasa A.; Santamaría L.; F. Escudero L.; F. Compañ A.; Pérez-Martín A. and (2010). SELECTING THE MOST ACCURATE FORECASTING METHOD FOR MEDICAL DIAGNOSIS. BREAST CANCER DIAGNOSIS - A Case Study.In Proceedings of the Third International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2010) ISBN 978-989-674-016-0, pages 142-148. DOI: 10.5220/0002590701420148

@conference{healthinf10,
author={Marc Almiñana and Alejandro Rabasa and Laureano Santamaría and Laureano {F. Escudero} and Antonio {F. Compañ} and Agustín Pérez{-}Martín},
title={SELECTING THE MOST ACCURATE FORECASTING METHOD FOR MEDICAL DIAGNOSIS. BREAST CANCER DIAGNOSIS - A Case Study},
booktitle={Proceedings of the Third International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2010)},
year={2010},
pages={142-148},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002590701420148},
isbn={978-989-674-016-0},
}

TY - CONF

JO - Proceedings of the Third International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2010)
TI - SELECTING THE MOST ACCURATE FORECASTING METHOD FOR MEDICAL DIAGNOSIS. BREAST CANCER DIAGNOSIS - A Case Study
SN - 978-989-674-016-0
AU - Almiñana, M.
AU - Rabasa, A.
AU - Santamaría, L.
AU - F. Escudero, L.
AU - F. Compañ, A.
AU - Pérez-Martín, A.
PY - 2010
SP - 142
EP - 148
DO - 10.5220/0002590701420148

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