Decision support system for breast cancer diagnosis by a meta-learning approach based on grammar evolution

Albert Fornells-Herrera, Elisabet Golobardes-Ribé, Ester Bernadó-Mansilla, Joan Martí-Bonmatí

Research output: Book chapterConference contributionpeer-review

6 Citations (Scopus)

Abstract

The incidence of breast cancer varies greatly among countries, but statistics show that every year 720,000 new cases will be diagnosed world-wide. However, a low percentage of women who suffer it can be detected using mammography methods. Therefore, it is necessary to develop new strategies to detect its formation in early stages. Many machine learning techniques have been applied in order to help doctors in the diagnosis decision process, but its definition and application are complex, getting results which are not often the desired. In this article we present an automatic way to build decision support systems by means of the combination of several machine learning techniques using a Meta-learning approach based on Grammar Evolution (MGE). We will study its application over different mammographic datasets to assess the improvement of the results.

Original languageEnglish
Title of host publicationICEIS 2006 - 8th International Conference on Enterprise Information Systems, Proceedings
Pages222-229
Number of pages8
Publication statusPublished - 2006
Event8th International Conference on Enterprise Information Systems, ICEIS 2006 - Paphos, Cyprus
Duration: 23 May 200627 May 2006

Publication series

NameICEIS 2006 - 8th International Conference on Enterprise Information Systems, Proceedings
VolumeAIDSS

Conference

Conference8th International Conference on Enterprise Information Systems, ICEIS 2006
Country/TerritoryCyprus
CityPaphos
Period23/05/0627/05/06

Keywords

  • Application of artificial intelligence on medicine
  • Breast cancer diagnosis
  • Evolutionary programming
  • Meta-Learning
  • Strategic decision support systems

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