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Engineering

Classification of Cancer Recurrence with Alpha-Beta BAM

Profile image of Elena AcevedoElena Acevedo

2009, Mathematical Problems in Engineering

https://doi.org/10.1155/2009/680212
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Abstract

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%.

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