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

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


Official URL: http://www.ukm.my/jsm/


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.

Item Type:Article
Keywords:ANFIS; clinicopathologic; genomic; oral cancer prognosis; ReliefF-GA
Journal:Sains Malaysiana
ID Code:7051
Deposited By: ms aida -
Deposited On:07 Apr 2014 07:31
Last Modified:14 Dec 2016 06:42

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