Home // COMPUTATION TOOLS 2013, The Fourth International Conference on Computational Logics, Algebras, Programming, Tools, and Benchmarking // View article
Prediction System of Larynx Cancer
Authors:
BenjamÃn Moreno-Montiel
Carlos Hiram Moreno-Montiel
Keywords: Data Minning; Classification; Classifier; Biochip genetic; Larynx Cancer.
Abstract:
In the task of data classification, there exist many uses and applications such as Credit assignment, Business, games Development, gene Research in public health problems, among others. In this research there is a large collection of data for treatment and prevention of some diseases, the most complex is the study of Cancer. The databases there have provided valuable knowledge useful for study of this disease that in many cases is unknown. An example of these databases is at the Centro Medico Nacional Siglo XXI, with information of human laryngeal carcinoma (LaCa). In this paper, we propose a Prediction System of Larynx Cancer (PSLC) to apply the task of classification of this type of databases to obtain novel knowledge for LaCa. The prediction system has two components, one component is the transformation and selection of data, the second component is a set of classifiers to obtain the prediction of life of sample patients with this type of cancer. With this prediction system, we found that, when there is an increase in CRBP-1 gene, it was correlated with patient survival; this allowed us to implement a Hybrid Classifier of Decision Rules (HCDR). The HCDR obtained the highest predictive value using genes CRBP-1 and provided a better degree of accuracy, with more than 90%, in comparison with different classifiers, indicating that the PSLC has a high degree of reliability.
Pages: 23 to 30
Copyright: Copyright (c) IARIA, 2013
Publication date: May 27, 2013
Published in: conference
ISSN: 2308-4170
ISBN: 978-1-61208-277-6
Location: Valencia, Spain
Dates: from May 27, 2013 to June 1, 2013