Cancer Detection Using Machine Learning: A Generalized Approach

Download PDF

Abstract

References

1. Nation Cancer Institute (NCI), Cancer – A detailed Guide http://cancer.gov/about-cancer, Accesed on March, 2016.
2. Konstantina Kourou, Themis P. Exarchos, Michalis V. Karamouzis, Machine learning applications in cancer prognosis and prediction, accesed on August, 2016
3. Ahrim Youn, Richard Simon, Identifying cancer driver genes in tumor genome sequencing studies, Bioinformatics. 2011 Jan 15; 27(2): 175–181.
4. UCI Machine Learning Repository of data sets for machine learning, http://archive.ics.uci.edu/ml/, Accesed at July, 2016
5. Data Catlog, Nation Cancer Institute R&D Resources, https://www.cancer.gov/research/resources/data-catalog, Accesed July 2016.
6. Ismail Saritas, Prediction of Breast Cancer using Artificial Neural Networks, Springer Science+Business Media, LLC 2011, Published on 12 August, 2011.
7. AS Ren J. 2012. ANN vs. SVM: Which One Performs Better in Classification of MCCs in Mammogram Imaging. Knowledge-Based Systems. 26: 144–153. 10 (1), January 2012.
8. I.S. Subashini T. S., V. Ramalingam, and S. Palanivel. 2009. Breast Mass Classification Based on Cytological Patterns using RBFNN and SVM. Expert Systems with Applications. 36: 5284–5290.
9. Ojha, Varun Kumar; Abraham, Ajith; Snášel, Václav (2017-04-01). 'Metaheuristic design of feedforward neural networks: A review of two decades of research'
10. Bottaci, Leonardo. 'Artificial Neural Networks Applied to Outcome Prediction for Colorectal Cancer Patients in Separate Institutions'.
11. Cortes, C.; Vapnik, V. (1995). 'Support-vector networks'. Machine Learning. 20 (3): 273–297.
12. O. L. Mangasarian and W. H. Wolberg: 'Cancer diagnosis via linear programming', SIAM News, Volume 23, Number 5, September 1990, pp 1 & 18.
13. William H. Wolberg and O.L. Mangasarian: 'Multisurface method of pattern separation for medical diagnosis applied to breast cytology', Proceedings of the National Academy of Sciences, U.S.A., Volume 87, December 1990, pp 9193-9196.
14. A Pär Stattin, Sigrid Carlsson, Benny Holmström, Andrew Vickers, Jonas Hugosson, Hans Lilja, Håkan Jonsson, Pro Prostate Cancer Mortality in Areas With High and Low Prostate Cancer Incidence https://academic.oup.com/jnci/article/doi/10.1093/jnci/dju007/1745564/Prostate-Cancer-Mortality-in-Areas-With-High-and
15. Liu Y., and Y. F. Zheng. 2004. FS_SFS: A Novel Feature Selection Method for Support Vector Machines. IEEE International Conference on Acoustic, Speech, and Signal Processing. 5: 797–800.
16. Keyvanfard F., M. A. Shoorehdeli, and M. Teshnehlab. 2011. Feature Selection and Classification of Breast Cancer on Dynamic Magnetic Resonance Imaging using ANN and SVM. American Journal of Biomedical Engineering. 1: 20–25.
17. Subashini T. S., V. Ramalingam, and S. Palanivel. 2009. Breast Mass Classification Based on Cytological Patterns using RBFNN and SVM . Expert Systems with Applications. 36: 5284–5290
18. Ren J. 2012. ANN vs. SVM: Which One Performs Better in Classification of MCCs in Mammogram Imaging. Knowledge-Based Systems. 26: 144–153
19. Altman, N. S. (1992). 'An introduction to kernel and nearest-neighbor nonparametric regression'. The American Statistician. 46 (3): 175–185.

Back