A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers

There are very few prognostic studies that combine both clinicopathologic and genomic data. Most of the studies use only clinicopathologic factors without taking into consideration the tumour biology and molecular information, while some studies use genomic markers or microarray information only wit...

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Main Authors:	Siow, Wee Chang, Sameem Abdul Kareem, Amir Feisal Merican Aljunid Merican, Rosnah Zain
Format:	Article
Language:	English
Published:	Universiti Kebangsaan Malaysia 2014
Online Access:	http://journalarticle.ukm.my/7051/ http://journalarticle.ukm.my/7051/ http://journalarticle.ukm.my/7051/1/10_Siow_Wee_Chang.pdf

id	ukm-7051
recordtype	eprints
spelling	ukm-70512016-12-14T06:42:58Z http://journalarticle.ukm.my/7051/ A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers Siow, Wee Chang Sameem Abdul Kareem, Amir Feisal Merican Aljunid Merican, Rosnah Zain, There are very few prognostic studies that combine both clinicopathologic and genomic data. Most of the studies use only clinicopathologic factors without taking into consideration the tumour biology and molecular information, while some studies use genomic markers or microarray information only without the clinicopathologic parameters. Thus, these studies may not be able to prognoses a patient effectively. Previous studies have shown that prognosis results are more accurate when using both clinicopathologic and genomic data. The objectives of this research were to apply hybrid artificial intelligent techniques in the prognosis of oral cancer based on the correlation of clinicopathologic and genomic markers and to prove that the prognosis is better with both markers. The proposed hybrid model consisting of two stages, where stage one with ReliefF-GA feature selection method to find an optimal feature of subset and stage two with ANFIS classification to classify either the patients alive or dead after certain years of diagnosis. The proposed prognostic model was experimented on two groups of oral cancer dataset collected locally here in Malaysia, Group 1 with clinicopathologic markers only and Group 2 with both clinicopathologic and genomic markers. The results proved that the proposed model with optimum features selected is more accurate with the use of both clinicopathologic and genomic markers and outperformed the other methods of artificial neural network, support vector machine and logistic regression. This prognostic model is feasible to aid the clinicians in the decision support stage and to identify the high risk markers to better predict the survival rate for each oral cancer patient. Universiti Kebangsaan Malaysia 2014-04 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/7051/1/10_Siow_Wee_Chang.pdf Siow, Wee Chang and Sameem Abdul Kareem, and Amir Feisal Merican Aljunid Merican, and Rosnah Zain, (2014) A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers. Sains Malaysiana, 43 (4). pp. 567-573. ISSN 0126-6039 http://www.ukm.my/jsm/
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	There are very few prognostic studies that combine both clinicopathologic and genomic data. Most of the studies use only clinicopathologic factors without taking into consideration the tumour biology and molecular information, while some studies use genomic markers or microarray information only without the clinicopathologic parameters. Thus, these studies may not be able to prognoses a patient effectively. Previous studies have shown that prognosis results are more accurate when using both clinicopathologic and genomic data. The objectives of this research were to apply hybrid artificial intelligent techniques in the prognosis of oral cancer based on the correlation of clinicopathologic and genomic markers and to prove that the prognosis is better with both markers. The proposed hybrid model consisting of two stages, where stage one with ReliefF-GA feature selection method to find an optimal feature of subset and stage two with ANFIS classification to classify either the patients alive or dead after certain years of diagnosis. The proposed prognostic model was experimented on two groups of oral cancer dataset collected locally here in Malaysia, Group 1 with clinicopathologic markers only and Group 2 with both clinicopathologic and genomic markers. The results proved that the proposed model with optimum features selected is more accurate with the use of both clinicopathologic and genomic markers and outperformed the other methods of artificial neural network, support vector machine and logistic regression. This prognostic model is feasible to aid the clinicians in the decision support stage and to identify the high risk markers to better predict the survival rate for each oral cancer patient.
format	Article
author	Siow, Wee Chang Sameem Abdul Kareem, Amir Feisal Merican Aljunid Merican, Rosnah Zain,
spellingShingle	Siow, Wee Chang Sameem Abdul Kareem, Amir Feisal Merican Aljunid Merican, Rosnah Zain, A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers
author_facet	Siow, Wee Chang Sameem Abdul Kareem, Amir Feisal Merican Aljunid Merican, Rosnah Zain,
author_sort	Siow, Wee Chang
title	A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers
title_short	A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers
title_full	A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers
title_fullStr	A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers
title_full_unstemmed	A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers
title_sort	hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers
publisher	Universiti Kebangsaan Malaysia
publishDate	2014
url	http://journalarticle.ukm.my/7051/ http://journalarticle.ukm.my/7051/ http://journalarticle.ukm.my/7051/1/10_Siow_Wee_Chang.pdf
first_indexed	2023-09-18T19:48:37Z
last_indexed	2023-09-18T19:48:37Z
_version_	1777406068903641088

A hybrid prognostic model for oral cancer based on clinicopathologic and genomic markers

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