Cervical cancer classification using convolutional neural network-support vector machine

Jane Eva Aurelia, Zuherman Rustam, Ilsya Wirasati

Research output: Contribution to journalArticlepeer-review

Abstract

Cervical cancer is the second most common cancer in women worldwide, and occurs when there are presences of abnormal cells in the cervix, which continue to grow uncontrollably. In the early stages, cervical cancer indications are not perceptible; however, it is easily detected with different forms of machine learning methods, such as the convolutional neural network (CNN). This is a popular method with a wide range of applications and known for its high accuracy value. Moreover, there is a support vector machine (SVM) with several kernel functions that is commonly used in the classification of diseases, and also known for its high accuracy value. Therefore, the combination of CNN-SVM with several linear kernels functions as classifier for the categorization of cervical cancer.

Original languageEnglish
Pages (from-to)1605-1611
Number of pages7
JournalTelkomnika (Telecommunication Computing Electronics and Control)
Volume19
Issue number5
DOIs
Publication statusPublished - 2021

Keywords

  • Cervical cancer
  • Classification
  • Convolutional neural network
  • Machine learning
  • Support vector machine

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