DocumentCode :
2387076
Title :
Lung carcinoma pigeonholing and vaticination by interspersed approach
Author :
Mathkour, Hassan ; Ahmad, Muneer
Author_Institution :
Dept. of Comput. Sci., King Saud Univ., Riyadh, Saudi Arabia
fYear :
2010
fDate :
17-18 March 2010
Firstpage :
264
Lastpage :
269
Abstract :
Vaticination and pigeonholing of lung carcinoma is a conspicuous nuisance for emancipate genesis. The carnage rate in elderly age is high as compared to younger ones and cure from carcinoma at premier stage is most salubrious. In this paper, we are proposing an interspersed and malleable approach for lung carcinoma pigeonholing and vaticination. The contrivance has been crumbled into laconic precincts that assimilate the visionary affirmation of pigeonholing and vaticination prodigy over training and testing datasets. This conviction serves as substratum for multi dimensional view/pigeonholing of aberrant datasets. We obtained 100 percent results for training confusion matrix and 83 percent for cross validation confusion matrix. The peerless least mean square error remained below 0.05 which shows a well trained architecture over multiple data segments.
Keywords :
bioinformatics; biological techniques; cancer; lung; carnage rate; cross validation confusion matrix; interspersed approach; laconic precinct; lung carcinoma; peerless least mean square error; pigeonholing; training confusion matrix; vaticination; Bayesian methods; Classification algorithms; Equations; Error analysis; Lungs; Medical diagnosis; Niobium; Supervised learning; Testing; Text categorization; bioinformatics; lung carcinoma; malleable; neural network; pigeonholing; vaticination;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Retrieval & Knowledge Management, (CAMP), 2010 International Conference on
Conference_Location :
Shah Alam, Selangor
Print_ISBN :
978-1-4244-5650-5
Type :
conf
DOI :
10.1109/INFRKM.2010.5466904
Filename :
5466904
Link To Document :
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