• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology

Article

Indian Journal of Science and Technology

Year: 2023, Volume: 16, Issue: 47, Pages: 4612-4619

Original Article

Classification of Breast Cancer Patients using Deep Learning Techniques

Received Date:01 November 2023, Accepted Date:22 November 2023, Published Date:30 December 2023

Abstract

Objectives: Breast cancer is one of the most ubiquitous cancers among women in the world and early exploration of the disease can be lifesaving. Finding breast cancer at an early stage enables quicker initiation of treatment, thereby enhancing the prospects of a positive outcome. Our aim is to identify the deep learning neural network model to classify breast cancer patients. Here, secondary open source data is considered to classify malignant and benign patients suitably. Methods: Deep learning neural network model, Artificial Neural Network and simulation approach is used to identify the more precise model. Findings: It is observed that, our proposed neural network model specified 97.5% accuracy. Efficiency of the proposed model is evaluated with the performance measures viz., MSE, RMSE etc. Novelty: The results of the study obtained through the proposed model express the efficiency of the model itself and also the superiority is demonstrated by comparing it with SVM, ANN, linear regression, 3DCNN deep models and existing works using various case studies. In the future, this model can be applicable in similar studies and it will give better results.

Keywords: Deep learning, Artificial Neural Network, Breast cancer, Classification, Wisconsin data set

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians. 2021;71(3):209–249. Available from: https://doi.org/10.3322/caac.21660
  2. Ghoushchi SJ, Ranjbarzadeh R, Najafabadi SA, Osgooei E, Tirkolaee EB. An extended approach to the diagnosis of tumour location in breast cancer using deep learning. Journal of Ambient Intelligence and Humanized. 2023;14:8487–8497. Available from: https://doi.org/10.1007/s12652-021-03613-y
  3. Gupta S, Gupta MK. Computational Model for Prediction of Malignant Mesothelioma Diagnosis. The Computer Journal. 2023;66(1):86–100. Available from: https://doi.org/10.1093/comjnl/bxab146
  4. Zhu W, Xie L, Han J, Guo X. The Application of Deep Learning in Cancer Prognosis Prediction. Cancers. 2020;12(3):1–19. Available from: https://doi.org/10.3390/cancers12030603
  5. Abunasser BS, Al-Hiealy MR, Zaqout IS, Abu-Naser SS. Convolution Neural Network for Breast Cancer Detection and Classification Using Deep Learning. Asian Pacific Journal of Cancer Prevention. 2023;24(2):531–544. Available from: https://journal.waocp.org/article_90487.html
  6. Xie J, Liu R, Luttrell J, Zhang C. Deep Learning Based Analysis of Histopathological Images of Breast Cancer. Frontiers in Genetics. 2019;10:1–19. Available from: https://doi.org/10.3389/fgene.2019.00080
  7. Chen H, Wang N, Du X, Mei K, Zhou Y, Cai G. Classification prediction of breast cancer based on machine learning. Computational Intelligence and Neuroscience. 2023;2023:1–9. Available from: https://doi.org/10.1155/2023/6530719
  8. Zakareya S, Izadkhah H, Karimpour J. A New Deep-Learning-Based Model for Breast Cancer Diagnosis from Medical Images. Diagnostics. 2023;13(11):1–23. Available from: https://doi.org/10.3390/diagnostics13111944
  9. Yari Y, Nguyen TV, Nguyen HT. Deep Learning Applied for Histological Diagnosis of Breast Cancer. IEEE Access. 2020;8:162432–162448. Available from: https://ieeexplore.ieee.org/document/9186080
  10. Gupta S, Gupta MK. A Comparative Analysis of Deep Learning Approaches for Predicting Breast Cancer Survivability. Archives of Computational Methods in Engineering. 2022;29(5):2959–2975. Available from: https://doi.org/10.1007/s11831-021-09679-3
  11. Islam MM, Haque MR, Iqbal H, Hasan MM, Hasan M, Kabir MN. Breast Cancer Prediction: A Comparative Study Using Machine Learning Techniques. SN Computer Science. 2020;1(5):1–14. Available from: https://doi.org/10.1007/s42979-020-00305-w
  12. Murtirawat R, Panchal S, Singh VK, Panchal Y. Breast Cancer Detection Using K-Nearest Neighbors, Logistic Regression and Ensemble Learning. In: 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC). Coimbatore, India, 02-04 July 2020. IEEE. p. 534–540.
  13. Arefan D, Mohamed AA, Berg WA, Zuley ML, Sumkin JH, Wu S. Deep learning modeling using normal mammograms for predicting breast cancer risk. Medical Physics. 2020;47(1):110–118. Available from: https://doi.org/10.1002/mp.13886
  14. Alfifi M, Shady M, Bataineh S, Mezher M. Enhanced Artificial Intelligence System for Diagnosing and Predicting Breast Cancer using Deep Learning. International Journal of Advanced Computer Science and Applications. 2020;11(7):498–513. Available from: https://thesai.org/Downloads/Volume11No7/Paper_63-Enhanced_Artificial_Intelligence_System.pdf
  15. Yala A, Lehman C, Schuster T, Portnoi T, Barzilay R. A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction. Radiology. 2019;292(1):60–66. Available from: https://doi.org/10.1148/radiol.2019182716
  16. Sharif MI, Li JP, Naz J, Rashid I. A comprehensive review on multi-organs tumor detection based on machine learning. Pattern Recognition Letters. 2020;131:30–37. Available from: https://doi.org/10.1016/j.patrec.2019.12.006
  17. Naji MA, Filali SE, Aarika K, Benlahmar EH, Abdelouhahid RA, Debauche O. Machine Learning Algorithms For Breast Cancer Prediction And Diagnosis. Procedia Computer Science. 2021;191:487–492. Available from: https://doi.org/10.1016/j.procs.2021.07.062
  18. Ragab DA, Sharkas M, Marshall S, Ren J. Breast cancer detection using deep convolutional neural networks and support vector machines. PeerJ. 2019;7:e6201. Available from: https://doi.org/10.7717/peerj.6201
  19. Wadkar K, Pathak P, Wagh N. Breast Cancer Detection Using ANN Network and Performance Analysis With SVM. International Journal of Computer Engineering and Technology. 2019;10(3):75–86. Available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3555041
  20. Fang Y, Zhao J, Hu L, Ying X, Pan Y, Wang X. Image classification toward breast cancer using deeply-learned quality features. Journal of Visual Communication and Image Representation. 2019;64:102609. Available from: https://doi.org/10.1016/j.jvcir.2019.102609

Copyright

© 2023 Navghare et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)

DON'T MISS OUT!

Subscribe now for latest articles and news.