Cancer is the most dreaded disease because it affects the human health severely. There are large number of cancer diseases. In thesetypes’ lung cancer is the major cause of mortality since it will not show its symptoms and signs of its presence. The lung cancer can be identified once it has spread the considerable extent in the body. Hence the prediction of lung cancer at an early stage is the toughest challenge that medical is facing. By predicting the lung cancer early, the step by step treatment can be planed which in turn will increase the patient’s chances of survival. It is mandatory to design a intelligent system that predicts the lung cancer accurate way and prediction to be done at the earlier stage.This research proposes algorithm that is based on Computed Aided Automated Classification using the computer that predicts the presence of cancer accurately at an earlier stage itself. In this frame work Back Propagation Neural Network classifier along with naturally inspiring Blue Whale Optimization algorithm is used. Though back propagation network performs efficient in classification it is having disadvantages of getting trapped in local minima because of its gradient based approach. This disadvantage is overcome by using meta heuristicblue whale optimization algorithm. In this algorithm local searching ability of Blue Whale Algorithm and global searching ability of BPN is combined together by which classification performance can be improved to a greater extent.Performing the classification and algorithm is tested and the results are compared with some of the traditional algorithm. This Prediction algorithm is helpful for the doctors for accurate prediction of the lung cancer at an earlier stage and a decision can be arrived about the extent of the treatment.
Volume 11 | 02-Special Issue
Pages: 1737-1748