Enhancing cancer diagnosis using spectroscopic information.

Cancer diagnosis is a very important process in the cancer treatment. With mass spectroscopic information, which characterizes the serum of the patients, the diagnostic process can be implemented more efficiently. As spectroscopic information is usually with a high dimension, statistic me...

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Main Author: Huang, Ke.
Other Authors: School of Chemical and Biomedical Engineering
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/16628
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-166282023-03-03T15:35:46Z Enhancing cancer diagnosis using spectroscopic information. Huang, Ke. School of Chemical and Biomedical Engineering Chen, Tao DRNTU::Engineering::Chemical engineering::Biotechnology Cancer diagnosis is a very important process in the cancer treatment. With mass spectroscopic information, which characterizes the serum of the patients, the diagnostic process can be implemented more efficiently. As spectroscopic information is usually with a high dimension, statistic methods are developed to reduce the dimension of the spectroscopy and reserve the information for analysis. Common methods of discriminant analysis include Fisher Discriminant Analysis (FDA), Partial Least Squares Discriminant Analysis (PLSDA) and Unsupervised Discriminant Projection (UDP). The applications of these methods to the cancer diagnosis process are described in this report. Supervised Discriminant Projection (SDP) based on UDP with supervised discriminant process instead was proposed. Comparisons were made among these methods with different parameters employed; and a most appropriate discriminant method was recommended at the end of the report. Bachelor of Engineering (Chemical and Biomolecular Engineering) 2009-05-27T07:35:38Z 2009-05-27T07:35:38Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/16628 en Nanyang Technological University 65 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Chemical engineering::Biotechnology
spellingShingle DRNTU::Engineering::Chemical engineering::Biotechnology
Huang, Ke.
Enhancing cancer diagnosis using spectroscopic information.
description Cancer diagnosis is a very important process in the cancer treatment. With mass spectroscopic information, which characterizes the serum of the patients, the diagnostic process can be implemented more efficiently. As spectroscopic information is usually with a high dimension, statistic methods are developed to reduce the dimension of the spectroscopy and reserve the information for analysis. Common methods of discriminant analysis include Fisher Discriminant Analysis (FDA), Partial Least Squares Discriminant Analysis (PLSDA) and Unsupervised Discriminant Projection (UDP). The applications of these methods to the cancer diagnosis process are described in this report. Supervised Discriminant Projection (SDP) based on UDP with supervised discriminant process instead was proposed. Comparisons were made among these methods with different parameters employed; and a most appropriate discriminant method was recommended at the end of the report.
author2 School of Chemical and Biomedical Engineering
author_facet School of Chemical and Biomedical Engineering
Huang, Ke.
format Final Year Project
author Huang, Ke.
author_sort Huang, Ke.
title Enhancing cancer diagnosis using spectroscopic information.
title_short Enhancing cancer diagnosis using spectroscopic information.
title_full Enhancing cancer diagnosis using spectroscopic information.
title_fullStr Enhancing cancer diagnosis using spectroscopic information.
title_full_unstemmed Enhancing cancer diagnosis using spectroscopic information.
title_sort enhancing cancer diagnosis using spectroscopic information.
publishDate 2009
url http://hdl.handle.net/10356/16628
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