Classification of Cancer Recurrence with Alpha-Beta BAM
Joint Authors
Acevedo, María Elena
Felipe, Federico
Acevedo, Marco Antonio
Source
Mathematical Problems in Engineering
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-10-19
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Bidirectional Associative Memories (BAMs) based on first model proposed by Kosko do not have perfect recall of training set, and their algorithm must iterate until it reaches a stable state.
In this work, we use the model of Alpha-Beta BAM to classify automatically cancer recurrence in female patients with a previous breast cancer surgery.
Alpha-Beta BAM presents perfect recall of all the training patterns and it has a one-shot algorithm; these advantages make to Alpha-Beta BAM a suitable tool for classification.
We use data from Haberman database, and leave-one-out algorithm was applied to analyze the performance of our model as classifier.
We obtain a percentage of classification of 99.98%.
American Psychological Association (APA)
Acevedo, María Elena& Acevedo, Marco Antonio& Felipe, Federico. 2009. Classification of Cancer Recurrence with Alpha-Beta BAM. Mathematical Problems in Engineering،Vol. 2009, no. 2009, pp.1-14.
https://search.emarefa.net/detail/BIM-489942
Modern Language Association (MLA)
Acevedo, María Elena…[et al.]. Classification of Cancer Recurrence with Alpha-Beta BAM. Mathematical Problems in Engineering No. 2009 (2009), pp.1-14.
https://search.emarefa.net/detail/BIM-489942
American Medical Association (AMA)
Acevedo, María Elena& Acevedo, Marco Antonio& Felipe, Federico. Classification of Cancer Recurrence with Alpha-Beta BAM. Mathematical Problems in Engineering. 2009. Vol. 2009, no. 2009, pp.1-14.
https://search.emarefa.net/detail/BIM-489942
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-489942
