Journal of Cybersecurity and Information Management JCIM 2690-6775 2769-7851 10.54216/JCIM https://www.americaspg.com/journals/show/798 2019 2019 American University in the Emirates, Dubai, United Arab Emirates Ahmed N. Al Masri LTU University of Technology, Sweden Hamam Mokayed Cervical cancer (CC) is the fourth commonly occurring cancer among females over the globe. It accounts for 7.9% of woman cancer as identified by world health organization (WHO). The most important reason for increased mortality due to cervical cancer is the deficiency of effective initial treatment. The asymptomatic nature is a main problem faced in the analysis of CC from initial stage. Recently, computer aided diagnosis (CAD) model has gained significant attention in the disease diagnostic process. At the same time, machine learning (ML) finds its use in several medical applications and is utilized as classifier for the initial detection of cancerous cells occurs from cervix area of uterus. With this motivation, this study introduces an intelligent ML based CAD (IML-CAD) technique to classify cervix cancer. The IML-CAD technique involves different stages of operations to detect and classify the cancerous cervix cells. In addition, the IML-CAD technique involves histogram based segmentation to determine the affected regions. Moreover, local binary patterns (LBP) based feature extractor and least squares support vector machine (LS-SVM) based classifier is designed for CC classification. To showcase the better performance of the IML-CAD technique, a series of simulations is performed and the experimental results highlighted the superior performance of the IML-CAD technique over the other techniques. 2020 2020 58 67 10.54216/JCIM.020203 https://www.americaspg.com/articleinfo/2/show/798