THE APPLICATION OF DEEP NEURAL NETWORK FOR BREAST CANCER CLASSIFICATION

Authors

  • Devi Nurtiyasari Department of Mathematic, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada
  • Abdurakhman Abdurakhman Department of Mathematic, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada
  • Muhamad Rashif Hilmi Department of Mathematic, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada

DOI:

https://doi.org/10.21831/jsd.v7i1.22237

Keywords:

breast cancer, Deep Neural Network

Abstract

Breast cancer is one of the most common cancers, especially for women. Early detection of breast cancer may increase the survival rate of patients significantly. Detecting breast cancer from breast image can be done by classification process. There are so many classification models which can be used for the classification process, such as neural network, fuzzy, neuro fuzzy, wavelet neural network, wavelet neuro fuzzy, etc. This research propose one of the neural network variant, i.e. Deep Neural Network. This kind of neural network model is using at least two hidden layers on the network. The more hidden layers used the deeper the neural network will be. The architecture of Deep Neural Network used in this research is feedforward network. Classification of breast tumor using Deep Neural Network model provides results with sensitivity, specificity, and accuracy were respectively 100%, 100%, and 66.67% for training data and 100%, 20%, and 60% for testing data.

 

Keywords: breast cancer, Deep Neural Network

Author Biographies

Devi Nurtiyasari, Department of Mathematic, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada

 

 

 

Abdurakhman Abdurakhman, Department of Mathematic, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada

devi.nurtiyasari@mail.ugm.ac.id

2 rachmanstat@ugm.ac.id

3 m.rashif@mail.ugm.ac.id

References

International Agency for Research on Cancer, World Cancer Report 2014, edited by Stewart, B.W. and Wild, C.P. (World Health Organization, Lyon, 2014), pp. 17-19.

Harralick, R.M. et al, Textural Feature for Image Classification. (IEEE Transaction on System, Man and Cybernetics. Vol. 3. No. 6., 1973). pp. 619.

Nielsen, M.A., Neural Networks and Deep Learning. (Determination Press, 2015).

Yeung. D.S, et al, Sensitivity Analysis for Neural Network. (Springer, Berlin, 2010). pp. 2.

Information Society Technology, The mini-MIAS Database of Mammograms. (2004)

Downloads

Published

2018-04-15

How to Cite

[1]
Nurtiyasari, D. et al. 2018. THE APPLICATION OF DEEP NEURAL NETWORK FOR BREAST CANCER CLASSIFICATION. Jurnal Sains Dasar. 7, 1 (Apr. 2018), 1–4. DOI:https://doi.org/10.21831/jsd.v7i1.22237.

Issue

Vol. 7 No. 1 (2018): April 2018

Section

Articles

License

Authors who publish with this journal agree to the following terms:

 

  1. Copyright of the published articles will be hold by the authors.

  2. Publisher of JSD is Universitas Negeri Yogyakarta

  3. The copyright follows Creative Commons Attribution–ShareAlike License (CC BY SA): This license allows to Share "” copy and redistribute the material in any medium or format, Adapt "” remix, transform, and build upon the material, for any purpose, even commercially.

 
 Creative Commons License