West Asia Organization for Cancer Prevention (WAOCP), APOCP's West Asia Chapter. Asian Pacific Journal of Cancer Prevention 1513-7368 20 7 2019 07 01 Lung Cancer Detection using Probabilistic Neural Network with modified Crow-Search Algorithm 2159 2166 88638 10.31557/APJCP.2019.20.7.2159 EN Sannasi Chakravarthy S R Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, India. 0000-0002-0162-7206 Harikumar Rajaguru Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, India. 0000-0002-2792-0945 Journal Article 2019 04 17 Objective: Lung cancer is a type of malignancy that occurs most commonly among men and the third most common<br />type of malignancy among women. The timely recognition of lung cancer is necessary for decreasing the effect of<br />death rate worldwide. Since the symptoms of lung cancer are identified only at an advanced stage, it is essential to<br />predict the disease at its earlier stage using any medical imaging techniques. This work aims to propose a classification<br />methodology for lung cancer automatically at the initial stage. Methods: The work adopts computed tomography (CT)<br />imaging modality of lungs for the examination and probabilistic neural network (PNN) for the classification task.<br />After pre-processing of the input lung images, feature extraction for the work is carried out based on the Gray-Level<br />Co-Occurrence Matrix (GLCM) and chaotic crow search algorithm (CCSA) based feature selection is proposed.<br />Results: Specificity, Sensitivity, Positive and Negative Predictive Values, Accuracy are the computation metrics used.<br />The results indicate that the CCSA based feature selection effectively provides an accuracy of 90%. Conclusion: The<br />strategy for the selection of appropriate extracted features is employed to improve the efficiency of classification and<br />the work shows that the PNN with CCSA based feature selection gives an improved classification than without using<br />CCSA for feature selection. https://journal.waocp.org/article_88638_4b96cdfd581afed1c63f3127de8a29b8.pdf