Cervical Cancer Risk Classification Based on Deep Convolutional Neural Network

Durrabida Zahras, Zuherman Rustam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

To meet the challenge of the increasing types of disease in this modern era, technology plays a very important role in health research. Women's health has become a major concern because of the increasing rates of cervical cancer because it can be a deadly disease. In this study, we will use deep convolutional neural networks to find the accuracy in classifying cervical cancer data on four different types of methods. The cervical cancer data are represented by 32 risk factors and four target variables: Hinselmann, Schiller, Cytology, and Biopsy. The result with deep learning method is quite encouraging, we can see that each data were correctly classified with the total accuracy reach almost 90% for each target.

Original languageEnglish
Title of host publicationProceedings of ICAITI 2018 - 1st International Conference on Applied Information Technology and Innovation
Subtitle of host publicationToward A New Paradigm for the Design of Assistive Technology in Smart Home Care
EditorsYance Sonatha, Rahmat Hidayat, Alde Alanda, MT Humaira, Indri Rahmayuni
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages149-153
Number of pages5
ISBN (Electronic)9781538667262
DOIs
Publication statusPublished - 10 Apr 2019
Event1st International Conference on Applied Information Technology and Innovation, ICAITI 2018 - Padang, Indonesia
Duration: 4 Sep 20185 Sep 2018

Publication series

NameProceedings of ICAITI 2018 - 1st International Conference on Applied Information Technology and Innovation: Toward A New Paradigm for the Design of Assistive Technology in Smart Home Care

Conference

Conference1st International Conference on Applied Information Technology and Innovation, ICAITI 2018
CountryIndonesia
CityPadang
Period4/09/185/09/18

Keywords

  • Cervical cancer
  • convolutional neural networks
  • deep learning

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  • Cite this

    Zahras, D., & Rustam, Z. (2019). Cervical Cancer Risk Classification Based on Deep Convolutional Neural Network. In Y. Sonatha, R. Hidayat, A. Alanda, MT. Humaira, & I. Rahmayuni (Eds.), Proceedings of ICAITI 2018 - 1st International Conference on Applied Information Technology and Innovation: Toward A New Paradigm for the Design of Assistive Technology in Smart Home Care (pp. 149-153). [8686767] (Proceedings of ICAITI 2018 - 1st International Conference on Applied Information Technology and Innovation: Toward A New Paradigm for the Design of Assistive Technology in Smart Home Care). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAITI.2018.8686767