Effective Diagnosis of Breast Cancer using KNN Algorithm

Deepali A. Patil*, Shakib Badarpura**, Abhishek Jain ***, Aniket Gupta****
*-**** Shree L.R. Tiwari College of Engineering, Maharashtra, India.
Periodicity:September - November'2019
DOI : https://doi.org/10.26634/jit.8.4.17241

Abstract

Cancer is one of the deadliest diseases in human beings. Breast cancer is considered to be the second most exposed cancer in the world and is now the most common disease in women. The women of ages 45-59 has the highest number of chances to be affected by breast cancer. Early prediction and diagnosis of breast cancer can prevent its spread and may help with effective treatment or medication. Predicting breast cancer is a very arduous task as the data can be highly Non-linear and may require high level computation modeling. However, many machine learning algorithms like KNN, K-Means, Decision Trees, Neural Networks etc., have proved to be effective in predicting breast cancer. This study shows the use of k-Nearest Neighbors (kNN) algorithm to predict whether a person is having breast cancer or not, using a machine learning model trained with different features. Thus, we inferred that we could predict the Breast Cancer with reasonable accuracy. From the results, it can be concluded that breast cancer cells can be accurately detected using machine learning techniques such as KNN.

Keywords

KNN, K-Means, Breast Cancer prediction, Machine Learning.

How to Cite this Article?

Patil, D. A., Badarpura, S., Jain, A., and Gupta, A. (2019). Effective Diagnosis of Breast Cancer using KNN Algorithm. i-manager's Journal on Information Technology, 8(4), 42-48. https://doi.org/10.26634/jit.8.4.17241

References

[1]. Al-hadidi, M. R., Alarabeyyat, A., & Alhanahnah, M. (2016). Breast cancer detection using K-nearest neighbor machine learning algorithm, In 9th International Conference on Developments in Systems Engineering (pp.35-39). https://doi.org/10.1109/DeSE.2016.8
[2]. Bayrak, E. A., Kırcı, P., & Ensari, T. (2019, April). Comparison of machine learning methods for breast cancer diagnosis. In 2019, Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT) (pp. 1-3). IEEE. https://doi.org/ 10.1109/EBBT.2019.8741990
[3]. Bharat, A., Pooja, N., & Reddy, R. A. (2018, October). Using Machine Learning algorithms for breast cancer risk rd prediction and diagnosis. In 2018, 3 International Conference on Circuits, Control, Communication and Computing (I4C) (pp. 1-4). IEEE. https://doi.org/10.1109/ CIMCA.2018.8739696
[4]. Jacob, D. S., Viswan, R., Manju, V., PadmaSuresh, L., & Raj, S. (2018, March). A survey on breast cancer prediction using data mining techniques. In 2018, Conference on Emerging Devices and Smart Systems (ICEDSS) (pp. 256-258). IEEE. https://doi.org/10.1109/ ICEDSS.2018.8544268
[5]. Nguyen, Q. H., T. Do, T. T., Wang, Y., Heng, S. S., Chen, K., Max Ang, W. H., Philip, C. E., Singh, M., Pham, H. N., Nguyen, B. P & H. Chua, M. C. (2019). Breast cancer prediction using feature selection and ensemble voting. In 2019, International Conference on System Science and Engineering (ICSSE). https://doi.org/10.1109/icsse. 2019.8823106
[6]. Pawlovsky, A. P., & Nagahashi, M. (2014). A method to select a good setting for the kNN algorithm when using it for breast cancer prognosis. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). https://doi.org/10.1109/bhi.2014.6864336
[7]. Sathiyanarayanan, P., Pavithra., S., Saranya., M. S., & Makeswari, M. (2019). Identification of breast cancer using the decision tree algorithm. In 2019, IEEE International Conference on System, Computation, Automation and Networking (ICSCAN). https://doi.org/10. 1109/icscan.2019.8878757
[8]. Sharma, R. K., & Nair, A. R. (2019, May). Efficient Breast Cancer prediction using ensemble machine learning th models. In 2019, 4 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT) (pp. 100 - 104). IEEE. https://doi.org/10.1109/RTEICT46194.2019.9016968
[9]. Sharma, S., Aggarwal, A., & Choudhury, T. (2018, December). Breast cancer detection using machine learning algorithms. In 2018, International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS) (pp. 114-118). IEEE. https://doi.org/10. 1109/CTEMS.2018.8769187
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