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Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques

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Abstract

Cervical cancer growth is the fourth maximum of regular diseases in females. It is one of the sicknesses which is compromising ladies' wellbeing everywhere in the world and it is difficult to notice any sign in the beginning phase. But the screening process of cervical cancer sometimes is being hampered due to some social-behavioral factors. There is still a limited number of researches directed in cervical cancer identification dependent on the behavior and machine learning in the area of gynecology and computer science. In this research, we have proposed three machine learning models such as Decision Tree, Random Forest, and XGBoost to predict cervical cancer from behavior and its variables and we got significantly improved outcomes than the current methods with 93.33% accuracy. Moreover, we have shown the top features from the dataset according to the feature important scores to know their impacts on the development of the classification model.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh

    Laboni Akter

  2. Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh

    Ferdib-Al-Islam, Md. Milon Islam & Md. Rezwanul Haque

  3. Research Chair of Pervasive and Mobile Computing, Information Systems Department, College of Computer and Information Sciences, King Saud University,, Riyadh, 11543, Saudi Arabia

    Mabrook S. Al-Rakhami

Authors
  1. Laboni Akter
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  2. Ferdib-Al-Islam
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  3. Md. Milon Islam
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  4. Mabrook S. Al-Rakhami
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  5. Md. Rezwanul Haque
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Correspondence to Mabrook S. Al-Rakhami.

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This article is part of the topical collection “Advances in Computational Approaches for Artificial Intelligence, Image Processing, IoT and Cloud Applications” guest edited by Bhanu Prakash K N and M. Shivakumar.

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Akter, L., Ferdib-Al-Islam, Islam, M.M. et al. Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques. SN COMPUT. SCI. 2, 177 (2021). https://doi.org/10.1007/s42979-021-00551-6

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  • DOI: https://doi.org/10.1007/s42979-021-00551-6

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