Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/22837
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Type: Conference paper
Title: T-ray relevant frequencies for osteosarcoma classification
Author: Withayachumnankul, W.
Ferguson, B.
Rainsford, T.
Findlay, D.
Mickan, S.
Abbott, D.
Citation: Proceedings of Microelectronics, MEMS, and Nanotechnology 2005, 2006 / Bell, J.M., Varadan, V.K. (ed./s), vol.6038, pp.60381H-1-60381H-15
Publisher: SPIE
Publisher Place: http://www.spie.org/conferences/programs/05/au/
Issue Date: 2006
Series/Report no.: Proceedings of SPIE--The International Society for Optical Engineering ; 6038
ISBN: 0819460699
9780819460691
ISSN: 0277-786X
Conference Name: SPIE Microelectronics, MEMS, and Nanotechnology (11 Dec 2005 : Brisbane, Australia)
Statement of
Responsibility: 
W. Withayachumnankul, B. Ferguson, T. Rainsford, D. Findlay, S. P. Mickan, and D. Abbott
Abstract: We investigate the classification of the T-ray response of normal human bone cells and human osteosarcoma cells, grown in culture. Given the magnitude and phase responses within a reliable spectral range as features for input vectors, a trained support vector machine can correctly classify the two cell types to some extent. Performance of the support vector machine is deteriorated by the curse of dimensionality, resulting from the comparatively large number of features in the input vectors. Feature subset selection methods are used to select only an optimal number of relevant features for inputs. As a result, an improvement in generalization performance is attainable, and the selected frequencies can be used for further describing different mechanisms of the cells, responding to T-rays. We demonstrate a consistent classification accuracy of 89.6%, while the only one fifth of the original features are retained in the data set.
Description: © 2006 COPYRIGHT SPIE--The International Society for Optical Engineering
RMID: 0020060862
DOI: 10.1117/12.637964
Appears in Collections:Electrical and Electronic Engineering publications

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