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Exploring the Behavioural Factors of Cervical Cancer Using ANOVA and Machine Learning Techniques

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Science, Engineering Management and Information Technology (SEMIT 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1808))

Abstract

Cervical cancer is the fourth most common and one of the deadliest types of cancer in the female population. However, it does not show any symptoms in the first stage. Therefore, early diagnosis is very difficult. On the other hand, there are some risk factors directly or indirectly associated with it. The effect of these risk factors on predicting the diagnosis of cervical cancer was investigated with machine learning-based algorithms and promising results were obtained. However, studies on which risk factors are more effective than others are scarce. This study focuses on investigating how the selection of promising factors associated with cervical cancer will affect the predictive ability of machine learning-based classification algorithms such as Gaussian Naive Bayes (GNB), k Nearest Neighbor and Decision Tree. ANOVA F-test is applied to evaluate each risk factor independently according to the desired class. In order to ensure the reliability of the results, K-fold cross validation technique is used at different K values. In the selected cervical cancer behavioral risk dataset, the GNB algorithm showed the highest performance (%94) with eight risk factors for all K values.

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Authors and Affiliations

  1. Istanbul Nisantasi University, 34398, Istanbul, Turkey

    Maide Çakır

  2. Ankara Yıldırım Beyazıt University, 06010, Ankara, Turkey

    Ali Degirmenci & Omer Karal

Authors
  1. Maide Çakır
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  2. Ali Degirmenci
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  3. Omer Karal
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Corresponding author

Correspondence to Maide Çakır .

Editor information

Editors and Affiliations

  1. Kharazmi University, Tehran, Iran

    Abolfazl Mirzazadeh

  2. Ankara Yıldırım Beyazıt University, Ankara, Türkiye

    Babek Erdebilli

  3. Istinye University, Istanbul, Türkiye

    Erfan Babaee Tirkolaee

  4. Poznań University of Technology, Poznań, Poland

    Gerhard-Wilhelm Weber

  5. Indian Institute of Technology Delhi, New Delhi, India

    Arpan Kumar Kar

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Çakır, M., Degirmenci, A., Karal, O. (2023). Exploring the Behavioural Factors of Cervical Cancer Using ANOVA and Machine Learning Techniques. In: Mirzazadeh, A., Erdebilli, B., Babaee Tirkolaee, E., Weber, GW., Kar, A.K. (eds) Science, Engineering Management and Information Technology. SEMIT 2022. Communications in Computer and Information Science, vol 1808. Springer, Cham. https://doi.org/10.1007/978-3-031-40395-8_18

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  • DOI: https://doi.org/10.1007/978-3-031-40395-8_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-40394-1

  • Online ISBN: 978-3-031-40395-8

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