Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer

Ammar Odeh; Ibrahim Al Atoum; Abrahim Bustanji

doi:doi:10.11648/j.jctr.20170502.13

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Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer

Ammar Odeh, Ibrahim Al Atoum, Abrahim Bustanji

Published in Journal of Cancer Treatment and Research (Volume 5, Issue 2)

Received: 29 October 2016 Accepted: 14 March 2017 Published: 22 March 2017

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Abstract

Nowadays, many researchers try to find out a system that enables to detect and expect diseases early so as to find the appropriate precaution or medical treatment of it. One of the leading causes of death worldwide is Cancer. Most of the deaths from this disease are due to late prediction and detection. According to the American Cancer Society (ACS); lung cancer is the second most common cancer; it accounts for about 13% of all new cancers. It is expected to have a 221, 200 new cases of lung cancer in 2015 with 158, 040 estimated deaths from lung Cancer [1]. The main objective of this study is to reach the highest accuracy and speed of its predecessors and this is what has been obtained.

Published in	Journal of Cancer Treatment and Research (Volume 5, Issue 2)
DOI	10.11648/j.jctr.20170502.13
Page(s)	15-18
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Cancer, Crossover, Mutation, Genetic Algorithm, WEKA, OWL

References

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[2]	F. Taher and R. Sammouda, "Lung cancer detection by using artificial neural network and fuzzy clustering methods," in GCC Conference and Exhibition (GCC), 2011 IEEE, 2011, pp. 295-298.
[3]	M. V. A. Gajdhane and L. Deshpande, "Detection of Lung Cancer Stages on CT scan Images by Using Various Image Processing Techniques."
[4]	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.
[5]	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.
[6]	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.
[7]	M. S. AL-TARAWNEH, "Lung Cancer Detection Using Image Processing Techniques," Leonardo Electronic Journal of Practices and Technologies, vol. 11, pp. 147-58, 2012.
[8]	J. Schneider, G. Peltri, N. Bitterlich, K. Neu, H.-G. Velcovsky, H. Morr, N. Katz, and E. Eigenbrodt, "Fuzzy logic-based tumor marker profiles including a new marker tumor M2-PK improved sensitivity to the detection of progression in lung cancer patients," Anticancer research, vol. 23, pp. 899-906, 2002.
[9]	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.
[10]	M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten, "The WEKA data mining software: an update," ACM SIGKDD explorations newsletter, vol. 11, pp. 10-18, 2009.
[11]	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.
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APA Style

Ammar Odeh, Ibrahim Al Atoum, Abrahim Bustanji. (2017). Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer. Journal of Cancer Treatment and Research, 5(2), 15-18. https://doi.org/10.11648/j.jctr.20170502.13

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ACS Style

Ammar Odeh; Ibrahim Al Atoum; Abrahim Bustanji. Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer. J. Cancer Treat. Res. 2017, 5(2), 15-18. doi: 10.11648/j.jctr.20170502.13

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AMA Style

Ammar Odeh, Ibrahim Al Atoum, Abrahim Bustanji. Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer. J Cancer Treat Res. 2017;5(2):15-18. doi: 10.11648/j.jctr.20170502.13

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@article{10.11648/j.jctr.20170502.13,
  author = {Ammar Odeh and Ibrahim Al Atoum and Abrahim Bustanji},
  title = {Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer},
  journal = {Journal of Cancer Treatment and Research},
  volume = {5},
  number = {2},
  pages = {15-18},
  doi = {10.11648/j.jctr.20170502.13},
  url = {https://doi.org/10.11648/j.jctr.20170502.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jctr.20170502.13},
  abstract = {Nowadays, many researchers try to find out a system that enables to detect and expect diseases early so as to find the appropriate precaution or medical treatment of it. One of the leading causes of death worldwide is Cancer. Most of the deaths from this disease are due to late prediction and detection. According to the American Cancer Society (ACS); lung cancer is the second most common cancer; it accounts for about 13% of all new cancers. It is expected to have a 221, 200 new cases of lung cancer in 2015 with 158, 040 estimated deaths from lung Cancer [1]. The main objective of this study is to reach the highest accuracy and speed of its predecessors and this is what has been obtained.},
 year = {2017}
}

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TY  - JOUR
T1  - Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer
AU  - Ammar Odeh
AU  - Ibrahim Al Atoum
AU  - Abrahim Bustanji
Y1  - 2017/03/22
PY  - 2017
N1  - https://doi.org/10.11648/j.jctr.20170502.13
DO  - 10.11648/j.jctr.20170502.13
T2  - Journal of Cancer Treatment and Research
JF  - Journal of Cancer Treatment and Research
JO  - Journal of Cancer Treatment and Research
SP  - 15
EP  - 18
PB  - Science Publishing Group
SN  - 2376-7790
UR  - https://doi.org/10.11648/j.jctr.20170502.13
AB  - Nowadays, many researchers try to find out a system that enables to detect and expect diseases early so as to find the appropriate precaution or medical treatment of it. One of the leading causes of death worldwide is Cancer. Most of the deaths from this disease are due to late prediction and detection. According to the American Cancer Society (ACS); lung cancer is the second most common cancer; it accounts for about 13% of all new cancers. It is expected to have a 221, 200 new cases of lung cancer in 2015 with 158, 040 estimated deaths from lung Cancer [1]. The main objective of this study is to reach the highest accuracy and speed of its predecessors and this is what has been obtained.
VL  - 5
IS  - 2
ER  -

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Author Information

Ammar Odeh

Department of Computer Science and Information Systems, Al Maarefa Colleges for Science & Technology, Riyadh, Kingdom of Saudi Arabia
Ibrahim Al Atoum

Department of Computer Science and Information Systems, Al Maarefa Colleges for Science & Technology, Riyadh, Kingdom of Saudi Arabia
Abrahim Bustanji

Department of Medicine, College of Medicine, Almaarefa Colleges for Science and Technology, Riyadh, Saudi Arabia

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APA Style

Ammar Odeh, Ibrahim Al Atoum, Abrahim Bustanji. (2017). Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer. Journal of Cancer Treatment and Research, 5(2), 15-18. https://doi.org/10.11648/j.jctr.20170502.13

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ACS Style

Ammar Odeh; Ibrahim Al Atoum; Abrahim Bustanji. Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer. J. Cancer Treat. Res. 2017, 5(2), 15-18. doi: 10.11648/j.jctr.20170502.13

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AMA Style

Ammar Odeh, Ibrahim Al Atoum, Abrahim Bustanji. Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer. J Cancer Treat Res. 2017;5(2):15-18. doi: 10.11648/j.jctr.20170502.13

Copy | Download

@article{10.11648/j.jctr.20170502.13,
  author = {Ammar Odeh and Ibrahim Al Atoum and Abrahim Bustanji},
  title = {Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer},
  journal = {Journal of Cancer Treatment and Research},
  volume = {5},
  number = {2},
  pages = {15-18},
  doi = {10.11648/j.jctr.20170502.13},
  url = {https://doi.org/10.11648/j.jctr.20170502.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jctr.20170502.13},
  abstract = {Nowadays, many researchers try to find out a system that enables to detect and expect diseases early so as to find the appropriate precaution or medical treatment of it. One of the leading causes of death worldwide is Cancer. Most of the deaths from this disease are due to late prediction and detection. According to the American Cancer Society (ACS); lung cancer is the second most common cancer; it accounts for about 13% of all new cancers. It is expected to have a 221, 200 new cases of lung cancer in 2015 with 158, 040 estimated deaths from lung Cancer [1]. The main objective of this study is to reach the highest accuracy and speed of its predecessors and this is what has been obtained.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Novel Genetic Algorithm for Early Prediction and Detection of Lung Cancer
AU  - Ammar Odeh
AU  - Ibrahim Al Atoum
AU  - Abrahim Bustanji
Y1  - 2017/03/22
PY  - 2017
N1  - https://doi.org/10.11648/j.jctr.20170502.13
DO  - 10.11648/j.jctr.20170502.13
T2  - Journal of Cancer Treatment and Research
JF  - Journal of Cancer Treatment and Research
JO  - Journal of Cancer Treatment and Research
SP  - 15
EP  - 18
PB  - Science Publishing Group
SN  - 2376-7790
UR  - https://doi.org/10.11648/j.jctr.20170502.13
AB  - Nowadays, many researchers try to find out a system that enables to detect and expect diseases early so as to find the appropriate precaution or medical treatment of it. One of the leading causes of death worldwide is Cancer. Most of the deaths from this disease are due to late prediction and detection. According to the American Cancer Society (ACS); lung cancer is the second most common cancer; it accounts for about 13% of all new cancers. It is expected to have a 221, 200 new cases of lung cancer in 2015 with 158, 040 estimated deaths from lung Cancer [1]. The main objective of this study is to reach the highest accuracy and speed of its predecessors and this is what has been obtained.
VL  - 5
IS  - 2
ER  -

Copy | Download