Prediction of Lung Cancer using Meta-Heuristic based Optimization Technique: Crow Search Technique
Saravanan Alagarsamy, R. Raja Subramanian, Theepika Shree, Soundarya kannan, Mounika Balasubramanian, Vishnuvarthanan Govindaraj
Abstract
In this paper, a meta-heuristic-based optimization technique is used for predicting cancer in the lungs. Lung cancer is one of the dreadful diseases that occurred in human beings and cause a lot of damage. Even though, lots of techniques have been proposed to predict lung cancer. But, still, the prediction of cancer has become a challenging task, due to the multifaceted structures in the CT scan. The automated meta-heuristic-based optimization technique namely crow search algorithm is used to find the feasible position and then searching the similar pixels for the clustering process. The exact position of the tumor is finding out using the crow search algorithm and can be better visualized. This process helps the radiologist to find the tumor in the beginning stage and acts as an efficient method for the prediction process. The sensitivity values (99.12 %) produced by the crow search technique is promising than the conventional techniques.