Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Artificial Intelligence and Software based models for Cancer Prediction System


Affiliations
1 Department of Computer Science, Fayoum University, Egypt
     

   Subscribe/Renew Journal


KDD is the process of turning the low – level data into high – level knowledge. Hence, KDD refers to the nontrivial extraction of implicit, previously unknown and potentially useful information from data in databases. While data mining and KDD are often treated as equivalent words but in real data mining is an important step in the KDD process.  In this study, we briefly examine the potential use of classification based data mining techniques such as Rule Based, Decision tree, Naïve Bayes and Artificial Neural Network to massive volume of healthcare data which, unfortunately, are not “mined” to discover hidden information. In this paper, AI techniques are applied for cancer prediction systems and a comparative analysis is presented.


Keywords

Cancer Prediction, Software Prediction Models, Artificial Machine Learning Techniques.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 194

PDF Views: 0




  • Artificial Intelligence and Software based models for Cancer Prediction System

Abstract Views: 194  |  PDF Views: 0

Authors

F. Werblin
Department of Computer Science, Fayoum University, Egypt
X. Zhu
Department of Computer Science, Fayoum University, Egypt

Abstract


KDD is the process of turning the low – level data into high – level knowledge. Hence, KDD refers to the nontrivial extraction of implicit, previously unknown and potentially useful information from data in databases. While data mining and KDD are often treated as equivalent words but in real data mining is an important step in the KDD process.  In this study, we briefly examine the potential use of classification based data mining techniques such as Rule Based, Decision tree, Naïve Bayes and Artificial Neural Network to massive volume of healthcare data which, unfortunately, are not “mined” to discover hidden information. In this paper, AI techniques are applied for cancer prediction systems and a comparative analysis is presented.


Keywords


Cancer Prediction, Software Prediction Models, Artificial Machine Learning Techniques.