Abstract
This paper presents an approach to cancer classification from gene expression profiling using cascaded neural network classifier. The method used aims to reduce the genes required to successfully classify the small round blue cell tumours of childhood (SRBCT) into four categories. The system designed to do this consists of a feedforward neural network and is trained with genetic algorithm. A concept of ‘gene masking’ is introduced to the system which significantly reduces the number of genes required for producing very high accuracy classification.
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Kumar, R., Chand, K., Lal, S.P. (2014). Gene Reduction for Cancer Classification Using Cascaded Neural Network with Gene Masking. In: Sokolova, M., van Beek, P. (eds) Advances in Artificial Intelligence. Canadian AI 2014. Lecture Notes in Computer Science(), vol 8436. Springer, Cham. https://doi.org/10.1007/978-3-319-06483-3_29
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DOI: https://doi.org/10.1007/978-3-319-06483-3_29
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06482-6
Online ISBN: 978-3-319-06483-3
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