International Journal of Information Engineering and Electronic Business(IJIEEB)
ISSN: 2074-9023 (Print), ISSN: 2074-9031 (Online)
Published By: MECS Press
IJIEEB Vol.10, No.5, Sep. 2018
A Study on Test Variable Selection and Balanced Data for Cervical Cancer Disease
Full Text (PDF, 519KB), PP.1-7
Cancer is a pestilent disease. One of the most important cancer kinds, cervical cancer is a malignant tumor which threats women's life. In this study, the importance of test variables for cervical cancer disease is investigated by utilizing Stability Selection method. Also, Random Under-Sampling and Random Over-Sampling methods are implemented on the dataset. In this context, the learning model is designed by using Random Forest algorithm. The experimental results show that Stability Selection, Random Over-Sampling and Random Forest based model are more successful, approximately 98% accuracy.
Cite This Paper
Kemal Akyol," A Study on Test Variable Selection and Balanced Data for Cervical Cancer Disease", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.10, No.5, pp. 1-7, 2018. DOI: 10.5815/ijieeb.2018.05.01
E.L. Dickson, R.I. Vogel, X. Luo, L.S. Downs, “Recent trends in typespecific HPV infection rates in the United States,” Epidemiol Infect, vol. 143, no. 5, pp. 1042-1047, 2015.
O.W. Brawley and S.G. Cowal, “Civil society’s role in efforts to control women’s cancers,” Lancet, vol. 389, no. 10071, pp. 775-776, 2017.
I.D. Duncan, “Cervical screening,” The Obstetrician & Gynaecologist, vol. 6, no. pp. 93–97, 2004.
H. Demirhindi, E. Nazlıcan, M. Akbaba, “Cervical cancer screening in Turkey: A community-based experience after 60 years of Pap smear usage,” Asian Pac J Cancer P, vol. 13, no.12, pp. 6497-6500, 2012.
“Turkish Cervical Cancer and Cervical Cytology Research Group. Prevalence of cervical cytological abnormalities in Turkey,” Int J Gynaecol Obstet, vol. 106, no.3, pp. 206-209, 2009.
N. Gökgöz and D. Aktaş, “Determination of women awareness level of cervical cancer & conducting Pap-Smear Test,” Yildirim Beyazit Universitesi Hemşirelik E-Dergisi, vol. 3, pp.11-23, 2015.
G. Ruzigana, L. Bazzet-Matabele, S. Rulisa, A.N. Martin, R.G. Ghebre, “Cervical cancer screening at a tertiary care center in Rwanda,” Gynecol Oncol Rep, vol. 21, pp.13-16, 2017.
M. Başaran, A. Başaran and Z. Küçükaydın, “Restaging in cervical cancer,” Turkiye Klinikleri J Gynecol Obst-Special Topics, vol. 8, no.1, pp. 117-127, 2015.
C. Eroglu, R. Keşli, M.A. Eryılmaz, Y. Ünlü, O. Gönenç, Ç. Çelik, “Serviks kanseri için riskli olan kadınlarda HPV tiplendirmesi ve HPV sıklığının risk faktörleri ve servikal smearle ilişkisi,” Nobel Medicus, vol. 7, no.3, pp.72-77, 2011.
L.H. Aktun, Y. Aykanat, F. Gökdağlı-Sağır, “Are cervicovaginal smear tests reliable during pregnancy?” Medeniyet Medical Journal, vol. 32, no.2, pp. 111-114, 2017.
L. Denny, S. de Sanjose, M. Mutebi, B.O. Anderson, Kim J, Jeronimo J, Herrero R, Yeates K, O. Ginsburg, R. Sankaranarayanan, “Interventions to close the divide for women with breast and cervical cancer between low-income and middle-income countries and high-income countries,” Lancet, vol. 389, no. 10071, pp.861-870, 2017.
B.F. Lees, B.K. Erickson, W.K. Huh, “Cervical cancer screening: evidence behind the guidelines,” Am J Obstet Gynecol, vol. 214, no.4, pp. 438-443, 2016.
E. Nazlıcan, M. Akbaba, H. Koyuncu, N. Savaş, B. Karaca, “Cervical cancer screening between 35-40 aged women at Kisecik region of Hatay provinence,” TAF Preventive Medicine Bulletin, vol.9, no.5, pp. 471-474, 2010.
E. Fusco, F. Padula, E. Mancini, A. Cavalieri, G. Grubisic, “History of colposcopy: a brief biography of Hinselmann,” Journal of Prenatal Medicine, vol. 2, no.2, pp. 19-23, 2008.
A. Singer, J.M. Monaghan, S.C. Quek, “Lower genital tract precancer colposcopy, pathology and treatment,” 2nd ed. Wiley: Blackwell Science, 2008.
J.S. Bentz, “Liquid-based cytology for cervical cancer screening,” Expert Rev Mol Diagn, vol. 5, no.6, pp. 857-871, 2005.
S.B. Kaveri, S. Khandelwal, “Role of Pap smear N cervical biopsy in unhealthy cervix,” Journal of Scientific and Innovative Research, vol.4, no.1, pp.4-9, 2015.
D.J. Dittman, T.M. Khoshgoftaar, R. Wald, A. Napolitano, “Comparison of data sampling approaches for imbalanced bioinformatics data,” Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference, May 21-23, Florida, 2014.
A.O. Durahim, “Comparison of sampling techniques for imbalanced learning,” Yönetim Bilişim Sistemleri Dergisi, vol. 1, no. 3, pp. 181-191, 2016.
U. R. Salunkhe, S. N. Mali, "A Hybrid Approach for Class Imbalance Problem in Customer Churn Prediction: A Novel Extension to Under-sampling", International Journal of Intelligent Systems and Applications (IJISA), Vol.10, No.5, pp.71-81, 2018. DOI: 10.5815/ijisa.2018.05.08
T. Sumadhi, M. Hemalatha, “An Enhanced Approach for Solving Class Imbalance Problem in Automatic Image Annotation,” International Journal of Image, Graphics and Signal Processing (IJIGSP), vol.5, no.2, pp.9-16, 2013.DOI: 10.5815/ijigsp.2013.02.02
H. Kaur, Er. P. Verma, “E-Mail Spam Detection Using Refined MLP with Feature Selection,” International Journal of Modern Education and Computer Science (IJMECS), vol.9, no.9, pp. 42-52, 2017. DOI: 10.5815/ijmecs.2017.09.05
S. Goswami, S. Chakraborty, H. N. Saha, "An Univariate Feature Elimination Strategy for Clustering Based on Metafeatures", International Journal of Intelligent Systems and Applications (IJISA), vol.9, no.10, pp.20-30, 2017. DOI: 10.5815/ijisa.2017.10.03
F. Mordelet, J. Horton, A.J. Hartemink, B.E. Engelhardt and R. Gordân, “Stability selection for regression-based models of transcription factor–DNA binding specificity,” Bioinformatics, vol. 29, no.13, pp. i117–i125, 2013.
M. Kumar, A.J. Singh, "Evaluation of Data Mining Techniques for Predicting Student’s Performance", International Journal of Modern Education and Computer Science (IJMECS), Vol.9, No.8, pp.25-31, 2017.DOI: 10.5815/ijmecs.2017.08.04
L. Breiman, “Random forests,” Mach Learn, vol. 45, pp. 5-32, 2001.
O. Akar and O. Gungor, “Classification of multispectral images using random forest algorithm,” Journal of Geodesy and Geoinformation, vol. 1, pp. 139-146, 2012.
S.A. Shaikh, Measures derived from a 2x2 table for an accuracy of a diagnostic test. J Biom Biostat, vol. 2, no. 128, pp. 1-4, 2011.