Genetic Algorithm for Detection of Cancer

Authors(3) :-Sujata R. Jadhao, Akangsha Gawai, Prof. Chhajed

One of the major disease is cancer. Several deaths occur due to overdue of detection of this disease. At present, several researchers trying to find the appropriate system to detect the diseases early, so as to find medical treatment of it. The Genetic Algorithm(GA) is one of the optimization method. The first part of this shebang briefly traces their theory , explain essential concept and deliberate theoretical aspects. The second part center at an detailed implementation of GA. Its discuss the population, selection, crossover and mutation also implementation of image in GA to detect cancer tumor. Genetic Algorithm is used to produce new generation by using crossover operation and also to do some modification on new generation. It gives good detection rate.

Authors and Affiliations

Sujata R. Jadhao
Information Technology, Anuradha Engineering college, Chikhli, Maharashtra, India
Akangsha Gawai
Information Technology, Anuradha Engineering college, Chikhli, Maharashtra, India
Prof. Chhajed
Information Technology, Anuradha Engineering college, Chikhli, Maharashtra, India

Cancer, Genetic Algorithm, Crossover, Mutation

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  8. Banzhaf, Wolfgang; Nordin, Peter; Keller, Robert; Francone, Frank,"Genetic Programming: An Introduction, Morgan Kaufmann, San Francisco, CA, 1998.
  9. S. Thrun. Learning to Play the Game of Chess. In G. Tesauro, D. Touretzky, and T. Leen, editors, Advances in Neural Information Processing Systems (NIPS) 7, Cambridge, MA, 1995. MIT Press. [
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  12. K.A. De Jong,"An analysis of the behavior of a class of genetic adaptive systems", Doctoral dissertation, University of Michigan, Ann Arbor, Michigan, 1975.
  13. H.J. Bremermann, J. Rogson, S. Salaff,"Global properties of evolution processes", In H.H. Pattee (ed.), Natural Automata and Useful Simulations, pp. 3–42, 1964.
  14. Lorenzen P., Joshi S., Gerig G., Bullitt E.,“Tumor-Induced Structural and Radiometric Asymmetry in Brain Images”, Proc the IEEE workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA), 1, pp. 488-501, 2001.
  15. N. Nandha Gopal , Dr. M. Karnan,“Diagnose Brain Tumor Through MRI Using Image Processing Clustering Algorithms Such As Fuzzy C Means Along With Intelligent Optimization Techniques”, 2010 IEEE.

Publication Details

Published in : Volume 5 | Issue 6 | January-February 2020
Date of Publication : 2020-02-17
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 173-179
Manuscript Number : IJSRST208634
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Sujata R. Jadhao, Akangsha Gawai, Prof. Chhajed, " Genetic Algorithm for Detection of Cancer", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 5, Issue 6, pp.173-179, January-February-2020.
Journal URL : https://ijsrst.com/IJSRST208634
Citation Detection and Elimination     |      | |
  • O. Abdoun, J. Abouchabaka, and C. Tajani, "Analyzing the Performance of Mutation Operators to Solve the Travelling Salesman Problem," arXiv preprint arXiv:1203.3099, 2012.
  • S. Peng, Q. Xu, X. B. Ling, X. Peng, W. Du, and L. Chen, "Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support vector machines," FEBS letters, vol. 555, pp. 358-362, 2003.
  • W. F. Baile, R. Buckman, R. Lenzi, G. Glober, E. A. Beale, and A. P. Kudelka, "SPIKES—a six-step protocol for delivering bad news: application to the patient with cancer," The oncologist, vol. 5, pp. 302-311, 2000.
  • M. S. AL-TARAWNEH, "Lung Cancer Detection Using Image Processing Techniques," Leonardo Electronic Journal of Practices and Technologies, vol. 11, pp. 147-58, 2012.
  • J. Schneider, N. Bitterlich, H.-G. Velcovsky, H. Morr, N. Katz, and E. Eigenbrodt, "Fuzzy logic-based tumor-marker profiles improved sensitivity in the diagnosis of lung cancer," International journal of clinical oncology, vol. 7, pp. 145-151, 2002.
  • A. Giatromanolaki, M. Koukourakis, E. Sivridis, H. Turley, K. Talks, F. Pezzella, K. Gatter, and A. Harris, "Relation of hypoxia inducible factor 1α and 2α in operable non-small cell lung cancer to angiogenic/molecular profile of tumours and survival," British journal of cancer, vol. 85, p. 881, 2001
  • Banzhaf, Wolfgang; Nordin, Peter; Keller, Robert; Francone, Frank,"Genetic Programming: An Introduction, Morgan Kaufmann, San Francisco, CA, 1998.
  • S. Thrun. Learning to Play the Game of Chess. In G. Tesauro, D. Touretzky, and T. Leen, editors, Advances in Neural Information Processing Systems (NIPS) 7, Cambridge, MA, 1995. MIT Press. [
  • J.H. Holland (1975),"Adaptation in Natural and Artificial Systems", University of Michigan Press, Ann Arbor, Michigan; re- issued by MIT Press 1992.
  • D.E. Goldberg,"Optimal initial population size for binarycoded genetic algorithms.TCGA Report 85001, University of Alabama, Tuscaloosa, 1985.
  • K.A. De Jong,"An analysis of the behavior of a class of genetic adaptive systems", Doctoral dissertation, University of Michigan, Ann Arbor, Michigan, 1975.
  • H.J. Bremermann, J. Rogson, S. Salaff,"Global properties of evolution processes", In H.H. Pattee (ed.), Natural Automata and Useful Simulations, pp. 3–42, 1964.
  • Lorenzen P., Joshi S., Gerig G., Bullitt E.,“Tumor-Induced Structural and Radiometric Asymmetry in Brain Images”, Proc the IEEE workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA), 1, pp. 488-501, 2001.
  • N. Nandha Gopal , Dr. M. Karnan,“Diagnose Brain Tumor Through MRI Using Image Processing Clustering Algorithms Such As Fuzzy C Means Along With Intelligent Optimization Techniques”, 2010 IEEE.
  • " target="_blank"> BibTeX
    |
  • O. Abdoun, J. Abouchabaka, and C. Tajani, "Analyzing the Performance of Mutation Operators to Solve the Travelling Salesman Problem," arXiv preprint arXiv:1203.3099, 2012.
  • S. Peng, Q. Xu, X. B. Ling, X. Peng, W. Du, and L. Chen, "Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support vector machines," FEBS letters, vol. 555, pp. 358-362, 2003.
  • W. F. Baile, R. Buckman, R. Lenzi, G. Glober, E. A. Beale, and A. P. Kudelka, "SPIKES—a six-step protocol for delivering bad news: application to the patient with cancer," The oncologist, vol. 5, pp. 302-311, 2000.
  • M. S. AL-TARAWNEH, "Lung Cancer Detection Using Image Processing Techniques," Leonardo Electronic Journal of Practices and Technologies, vol. 11, pp. 147-58, 2012.
  • J. Schneider, N. Bitterlich, H.-G. Velcovsky, H. Morr, N. Katz, and E. Eigenbrodt, "Fuzzy logic-based tumor-marker profiles improved sensitivity in the diagnosis of lung cancer," International journal of clinical oncology, vol. 7, pp. 145-151, 2002.
  • A. Giatromanolaki, M. Koukourakis, E. Sivridis, H. Turley, K. Talks, F. Pezzella, K. Gatter, and A. Harris, "Relation of hypoxia inducible factor 1α and 2α in operable non-small cell lung cancer to angiogenic/molecular profile of tumours and survival," British journal of cancer, vol. 85, p. 881, 2001
  • Banzhaf, Wolfgang; Nordin, Peter; Keller, Robert; Francone, Frank,"Genetic Programming: An Introduction, Morgan Kaufmann, San Francisco, CA, 1998.
  • S. Thrun. Learning to Play the Game of Chess. In G. Tesauro, D. Touretzky, and T. Leen, editors, Advances in Neural Information Processing Systems (NIPS) 7, Cambridge, MA, 1995. MIT Press. [
  • J.H. Holland (1975),"Adaptation in Natural and Artificial Systems", University of Michigan Press, Ann Arbor, Michigan; re- issued by MIT Press 1992.
  • D.E. Goldberg,"Optimal initial population size for binarycoded genetic algorithms.TCGA Report 85001, University of Alabama, Tuscaloosa, 1985.
  • K.A. De Jong,"An analysis of the behavior of a class of genetic adaptive systems", Doctoral dissertation, University of Michigan, Ann Arbor, Michigan, 1975.
  • H.J. Bremermann, J. Rogson, S. Salaff,"Global properties of evolution processes", In H.H. Pattee (ed.), Natural Automata and Useful Simulations, pp. 3–42, 1964.
  • Lorenzen P., Joshi S., Gerig G., Bullitt E.,“Tumor-Induced Structural and Radiometric Asymmetry in Brain Images”, Proc the IEEE workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA), 1, pp. 488-501, 2001.
  • N. Nandha Gopal , Dr. M. Karnan,“Diagnose Brain Tumor Through MRI Using Image Processing Clustering Algorithms Such As Fuzzy C Means Along With Intelligent Optimization Techniques”, 2010 IEEE.
  • " target="_blank">RIS
    |
  • O. Abdoun, J. Abouchabaka, and C. Tajani, "Analyzing the Performance of Mutation Operators to Solve the Travelling Salesman Problem," arXiv preprint arXiv:1203.3099, 2012.
  • S. Peng, Q. Xu, X. B. Ling, X. Peng, W. Du, and L. Chen, "Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support vector machines," FEBS letters, vol. 555, pp. 358-362, 2003.
  • W. F. Baile, R. Buckman, R. Lenzi, G. Glober, E. A. Beale, and A. P. Kudelka, "SPIKES—a six-step protocol for delivering bad news: application to the patient with cancer," The oncologist, vol. 5, pp. 302-311, 2000.
  • M. S. AL-TARAWNEH, "Lung Cancer Detection Using Image Processing Techniques," Leonardo Electronic Journal of Practices and Technologies, vol. 11, pp. 147-58, 2012.
  • J. Schneider, N. Bitterlich, H.-G. Velcovsky, H. Morr, N. Katz, and E. Eigenbrodt, "Fuzzy logic-based tumor-marker profiles improved sensitivity in the diagnosis of lung cancer," International journal of clinical oncology, vol. 7, pp. 145-151, 2002.
  • A. Giatromanolaki, M. Koukourakis, E. Sivridis, H. Turley, K. Talks, F. Pezzella, K. Gatter, and A. Harris, "Relation of hypoxia inducible factor 1α and 2α in operable non-small cell lung cancer to angiogenic/molecular profile of tumours and survival," British journal of cancer, vol. 85, p. 881, 2001
  • Banzhaf, Wolfgang; Nordin, Peter; Keller, Robert; Francone, Frank,"Genetic Programming: An Introduction, Morgan Kaufmann, San Francisco, CA, 1998.
  • S. Thrun. Learning to Play the Game of Chess. In G. Tesauro, D. Touretzky, and T. Leen, editors, Advances in Neural Information Processing Systems (NIPS) 7, Cambridge, MA, 1995. MIT Press. [
  • J.H. Holland (1975),"Adaptation in Natural and Artificial Systems", University of Michigan Press, Ann Arbor, Michigan; re- issued by MIT Press 1992.
  • D.E. Goldberg,"Optimal initial population size for binarycoded genetic algorithms.TCGA Report 85001, University of Alabama, Tuscaloosa, 1985.
  • K.A. De Jong,"An analysis of the behavior of a class of genetic adaptive systems", Doctoral dissertation, University of Michigan, Ann Arbor, Michigan, 1975.
  • H.J. Bremermann, J. Rogson, S. Salaff,"Global properties of evolution processes", In H.H. Pattee (ed.), Natural Automata and Useful Simulations, pp. 3–42, 1964.
  • Lorenzen P., Joshi S., Gerig G., Bullitt E.,“Tumor-Induced Structural and Radiometric Asymmetry in Brain Images”, Proc the IEEE workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA), 1, pp. 488-501, 2001.
  • N. Nandha Gopal , Dr. M. Karnan,“Diagnose Brain Tumor Through MRI Using Image Processing Clustering Algorithms Such As Fuzzy C Means Along With Intelligent Optimization Techniques”, 2010 IEEE.
  • " target="_blank">CSV

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