DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma

A tremendous amount of research has investigated carcinoma and looked into treatments to lower cancer mortality. Nevertheless, oral cancer is still a considerable health issue worldwide and mortality and incidence rates are rising. Oral cancer is ranked as the sixth most common carcinoma and is a pr...

Full description

Bibliographic Details
Main Authors:	Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah
Format:	Conference or Workshop Item
Language:	English
Published:	2015
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/48057/ http://irep.iium.edu.my/48057/ http://irep.iium.edu.my/48057/1/ID_125.pdf

id	iium-48057
recordtype	eprints
spelling	iium-480572018-05-23T02:35:00Z http://irep.iium.edu.my/48057/ DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma Zarzar, Mouayad Razak, Eliza Htike@Muhammad Yusof, Zaw Zaw Yusof, Faridah T Technology (General) A tremendous amount of research has investigated carcinoma and looked into treatments to lower cancer mortality. Nevertheless, oral cancer is still a considerable health issue worldwide and mortality and incidence rates are rising. Oral cancer is ranked as the sixth most common carcinoma and is a prime health dilemma globally. Thus, it is increasingly important to have tools that allow for discrimination between oral dysplasia and squamous-cell carcinoma. Although conventional methods such as medical imaging can be helpful in prediction and diagnosis of oral cancer, these methods continue to have limitations. More recently, machine learning has been used as a complementary approach in biomedical research and it now plays a leading role in the emerging domains of computational biology and bioinformatics. Specifically, DNA chip gene expression technology is currently helping researchers to distinguish oral dysplasia and squamous-cell carcinoma thru analysis of gene expression in tissue samples. Nonetheless, one of the prime challenges in the computational process of microarray data is the curse of dimensionality due to the crushing number of features. Therefore, we applied a random projection (RP) feature construction technique to tackle the problem of high-dimensional gene expression data and to increase the efficiency of our proposed model. In addition, we combined a RP technique with a support vector machine (SVM) that employs a sequential minimal optimization training algorithm (SMO) in order to efficiently differentiate squamous-cell carcinoma and oral dysplasia. The highest classification accuracy recorded by our proposed model was 95.6332%. We show in this study that using a SMO machine-learning classifier with a RP dimensionality reduction tool can be effective for classifying oral cancer. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/48057/1/ID_125.pdf Zarzar, Mouayad and Razak, Eliza and Htike@Muhammad Yusof, Zaw Zaw and Yusof, Faridah (2015) DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma. In: International Conference on Advances Technology in Telecommunication, Broadcasting, and Satellite, 26-27 Sep 2015, Jakarta, Indonesia. (In Press) http://telsatech.org/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Zarzar, Mouayad Razak, Eliza Htike@Muhammad Yusof, Zaw Zaw Yusof, Faridah DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma
description	A tremendous amount of research has investigated carcinoma and looked into treatments to lower cancer mortality. Nevertheless, oral cancer is still a considerable health issue worldwide and mortality and incidence rates are rising. Oral cancer is ranked as the sixth most common carcinoma and is a prime health dilemma globally. Thus, it is increasingly important to have tools that allow for discrimination between oral dysplasia and squamous-cell carcinoma. Although conventional methods such as medical imaging can be helpful in prediction and diagnosis of oral cancer, these methods continue to have limitations. More recently, machine learning has been used as a complementary approach in biomedical research and it now plays a leading role in the emerging domains of computational biology and bioinformatics. Specifically, DNA chip gene expression technology is currently helping researchers to distinguish oral dysplasia and squamous-cell carcinoma thru analysis of gene expression in tissue samples. Nonetheless, one of the prime challenges in the computational process of microarray data is the curse of dimensionality due to the crushing number of features. Therefore, we applied a random projection (RP) feature construction technique to tackle the problem of high-dimensional gene expression data and to increase the efficiency of our proposed model. In addition, we combined a RP technique with a support vector machine (SVM) that employs a sequential minimal optimization training algorithm (SMO) in order to efficiently differentiate squamous-cell carcinoma and oral dysplasia. The highest classification accuracy recorded by our proposed model was 95.6332%. We show in this study that using a SMO machine-learning classifier with a RP dimensionality reduction tool can be effective for classifying oral cancer.
format	Conference or Workshop Item
author	Zarzar, Mouayad Razak, Eliza Htike@Muhammad Yusof, Zaw Zaw Yusof, Faridah
author_facet	Zarzar, Mouayad Razak, Eliza Htike@Muhammad Yusof, Zaw Zaw Yusof, Faridah
author_sort	Zarzar, Mouayad
title	DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma
title_short	DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma
title_full	DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma
title_fullStr	DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma
title_full_unstemmed	DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma
title_sort	dna microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma
publishDate	2015
url	http://irep.iium.edu.my/48057/ http://irep.iium.edu.my/48057/ http://irep.iium.edu.my/48057/1/ID_125.pdf
first_indexed	2023-09-18T21:08:17Z
last_indexed	2023-09-18T21:08:17Z
_version_	1777411080511815680

DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma

Similar Items