Prediction of Cervical Cancer Using Chicken Swarm Optimization

Abstract

Chicken Swarm Optimization algorithm for feature selection is proposed in this paper, which can be used for the prediction of cervical cancer. Cervical Cancer is the type of cancer that occurs at the cells of the cervix-the lower part of the uterus-which connects the vagina. This kind of cancer is generally caused by several strains of the human papillomavirus (HPV), a sexually transmitted infection. Feature Selection is a tool of optimization algorithm and plays an active role in the area of machine learning. The amount of data available for processing in machine learning problems has increased rapidly in recent years. So, the feature selection was introduced to solve this problem. Feature Selection is used when there is a need to eliminate such redundant features so that a better subset of features can be obtained by which dimensionality of dataset is reduced considerably. The Chicken Swarm Optimization is an algorithm method inspired by nature, which is used for optimization techniques, proposed for feature selection for prediction of cervical cancer. Impersonating the hierarchical order in the Chicken Swarm, which includes hens, roosters, and chicks. CSO can productively extricate the chickens' swarm intelligence to optimize problems. CSO has the ability to attain exceptional optimization results in terms of optimization correctness. In CSO, the chicken swarm is divided into various sets or groups, which consist of a single rooster and a number of hens

Artificial Intelligence for Cervical Cancer Analysis

“…Pre-processing and features selection are two important steps to improve machine learning tasks. In this sense, [19] used a Chicken Swarm Optimization algorithm for feature selection for the prediction of CxCa. Similarly, [20] proposes an integrative machine learning approach to analyze multiple gene expression profiles in CxCa to identify genetic markers to help in the diagnosis or prognosis of this type of cancer.…”

“…Data from Swedish National Cervical Screening Registry, the Swedish Total Population Registry and the Swedish National Cancer Registry on individual level. [19] Chicken Swarm Optimization algorithm for feature selection, which can be used for the prediction of CxCa.…”

“…It was observed that the CxCa dataset collected from the Hospital Universitario de Caracas in Caracas, Venezuela, located in the UCI repository is widely used for research related to CxCa prediction. This dataset comprises statistic information, historic medical records and habits of 858 patients [19,21,32].  National Center for Biotechnology Information (NCBI) provides access to biomedical and genomic information.…”

“…[31], [29], [22], [24] Chicken Swarm Optimization [19] GNRBA method for solving cancer classification [32] Bayesian [13], [ Random walk with restart (RWR) Jaccard coefficient [30] Gene expression analysis [20] Fuzzy Logic [18] Statistical analysis, Pearson's Chi-squared test, and Kruskal-Wallis test [26], [14] It is not specified.…”

An Efficient Chicken Search Optimization Algorithm for the Optimal Design of Fuzzy Controllers

“…Other important contributions in which CSO algorithm has had an important presence is on the medical area. Some works include [18], where a comparative study of bioinspired algorithms applied in the optimization of fuzzy systems is presented by Miramontes et al,and [19], where a prediction of cervical cancer using Chicken Swarm Optimization is presented by Tripathi et al…”