Citation :

Proloy Kumar Mondal, Haewon Byeon, "Classification of Cervical Carcinoma: Employing Traditional Tree-Based Machine Learning Methods Utilizing Feature Selection Algorithms," International Journal of Engineering Trends and Technology (IJETT), vol. 74, no. 5, pp. 138-147, 2026. Crossref, https://doi.org/10.14445/22315381/IJETT-V74I5P109

Abstract

Set against the fact that Cervical Cancer (CC) is the second-highest cancer amongst women globally, the Pap smear is one of the most widely screened test systems today. The number of cases in Bangladesh is rising fast, an urgent problem. To address this problem, an increasing number of individuals and researchers are turning to Machine Learning (ML) and Deep Learning (DL) to process large amounts of data and produce insights that can be implemented. ML-powered methods for the early-stage prediction of critical illnesses such as cancer, kidney failure, and heart diseases are standard in healthcare today. The early detection of cervical cancer is a potential option for the prevention of this disease, which is a prevalent condition in females. We addressed this performance in a wrapper model with Metaheuristic Algorithms: Osprey Optimization Algorithm (OOA). Machine learning classifier for CC prediction in this paper, we used AdaBoost as the machine learning classifier for CC prediction. By keeping all the 36 features, we are getting with AdaBoost an accuracy of 96%, a precision of 97%, a recall of 98%, and an F1 score of around 98%. Also, we utilized the OOA algorithm to find a beneficial subset of features to assist in the important feature selection. An OOA method reduced the features from 36 to 7. These results demonstrate the possibility of early cervical cancer detection using a reduced feature set with retained prediction power. Critically, we produced an enumeration of essential features for cervical cancer derived from our optimization algorithm and addressed CPU time for cost-effectiveness.

Keywords

Cancer of the Cervical Region, Machine Learning, Metaheuristic Algorithm, AdaBoost Algorithm, Osprey Optimization Algorithm (OOA).

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