COMPUTATIONAL INTELLIGENCE SYSTEM FOR LOWER THE RISK OF COLORECTAL CANCER IN HIGH DIMENSIONAL DATA

Most dangerous cancer disease that causes deaths worldwide approximately 6, 00,000 is Colorectal Cancer (CRC). It is very crucial task to determine the cancer affecting factors effective and accurately. In Today's day-to-day life, physical analysis of medical images is difficult as the no of patient's increases and also it is time consuming, deadly and impractical. With the development of machine learning technology, it is possible to create a CAD system in order to make total recognition process easier, efficient and less time consumption trough proper utilization of resources. In the current scenario, Timely and accurate prediction of cancer is challenging issue. In this research, we projected a Computational Intelligence System for detecting colorectal cancer in high dimensional data. To corroborate the competence and proficiency of our predictable system, it is developed in open source called Weka tool. This research work offers a novel approach for colorectal cancer extrapolation based on correlated risky factors. Artificial Intelligence system and Convolutional methods are utilized and their presentations are equated. From the proportional exploration, it is perceived that the projected model outstrip total added classifiers and accomplishes imposing cut-off values through various enactment metrics such as Accuracy of 98 percentage Sensitivity of 97 percentage and 100 percentage of Specificity.