International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
Volume 123 - Issue 7 |
Published: August 2015 |
Authors: Harshnika Bhasin, Zuber Farooqui |
![]() |
Harshnika Bhasin, Zuber Farooqui . An Improved Pattern Mining Technique for Analysis of Prognostication of Breast Carcinoma Disease. International Journal of Computer Applications. 123, 7 (August 2015), 41-45. DOI=10.5120/ijca2015905440
@article{ 10.5120/ijca2015905440, author = { Harshnika Bhasin,Zuber Farooqui }, title = { An Improved Pattern Mining Technique for Analysis of Prognostication of Breast Carcinoma Disease }, journal = { International Journal of Computer Applications }, year = { 2015 }, volume = { 123 }, number = { 7 }, pages = { 41-45 }, doi = { 10.5120/ijca2015905440 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2015 %A Harshnika Bhasin %A Zuber Farooqui %T An Improved Pattern Mining Technique for Analysis of Prognostication of Breast Carcinoma Disease%T %J International Journal of Computer Applications %V 123 %N 7 %P 41-45 %R 10.5120/ijca2015905440 %I Foundation of Computer Science (FCS), NY, USA
This paper presents a study of different techniques of information mining algorithms used for the aim of predicting carcinoma because it is understood to any or all that prediction of carcinoma survivability has been a difficult research problem for several researchers. Since the early dates of the related analysis, a lot of advancement has been recorded in many related fields. For an instance, a sincere thanks to existing biomedical technologies, higher instructive prognostic factors are being measured and recorded; because of low value computer components and software system technologies, high volume good quality information is being collected and keep automatically; and at last thanks to higher analytical strategies, those voluminous information is being processed effectively and with efficiency. Therefore, the most objective of this manuscript is to report on a research project where we have a tendency to take advantage of these available technological advancements to develop prediction models for carcinoma survivability.