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Diferansiyel denklemler kullanarak meme kanserinin istatistik modellemesi

Statistical modeling of breast cancer using differential equations

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Abstract (2. Language): 
The object of the present study is to develop differential equations that will characterize the behavior of the tumor as a function of time. Having such differential equations, the solution of which once plotted will identify the rate of change of tumor size as a function of age. The structures of the differential equations characterize the growth of breast cancer tumor. Once we have developed the differential equations and their solutions, we proceed to validate the quality of the differential system and discuss its usefulness.
Abstract (Original Language): 
Sunulan bu çalısmanın amacı, tümor davranısını zamanın bir fonksiyonu olarak niteleyen diferansiyel denklemler gelistirmektir. Bu tanıma uyan farklı diferansiyel denklemler elde edilmis ve grafiksel olarak gösterilen denklemin sonucu, yasın fonksiyonu olarak tümör büyüklügünün degisim oranını belirlemede kullanılmıstır. Diferansiyel denklemlerin yapıları meme kanseri tümörünün gelisimini tanımlamaktadır. Diferansiyel denklemler ve çözümleri gelistirildikten sonra diferansiyel sistemin kalitesi dogrulanmıs ve yöntemin faydası tartısılmıstır.
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REFERENCES

References: 

[1] J. Sariego, Breast cancer in the young patient. The American Surgeon, 76, 12,
1397–1400 (2010).
[2] U.S. National Institutes of Health, http://seer.cancer.gov (2010).
[3] M.P. Madigan, R.G. Ziegler, J. Benichou, C. Byrne, and R.N. Hoover, Proportion of
breast cancer cases in the United States explained by well-established risk factors.
Journal of the National Cancer Institute. 87, 22, 1681–1685 (1995).
[4] D.P. Winchester, The National Cancer Data Base report on breast carcinoma
characteristics and outcome in relation to age. Cancer, 78, 1838 (1996).
[5] SA. Feig and RE. Hendrick, Radiation risk from screening mammography of women
aged 40–49 years. Journal of National Cancer Institute Monographs, 22, 22, 119–
124 (1997).
[6] S. Venturi, Is there a role for iodine in breast diseases? The Breast, 10, 5, 379–382
(2001).
[7] A.W. Fyles, D.R. McCready, and L.A. Manchul, Tamoxifen with or without breast
irradiation in women 50 years of age or older with early breast cancer. New
England Journal of Medicine, 351, 963-970 (2004).
[8] U.W. Jayasinghe, Is age at diagnosis an independent prognostic factor for survival
following breast cancer? Anz Journal of Surgery, 75, 762 (2005).
[9] R.T. Chlebowski, GL. Blackburn, and CA. Thomson, Dietary fat reduction and breast
cancer outcome: interim efficacy results from the Women's Intervention Nutrition
Study. Journal of the National Cancer Institute, 98, 24, 1767–1776 (2006).
[10] P. Boffetta, M. Hashibe, C. La Vecchia, W. Zatonski, and J. Rehm, The burden of
cancer attributable to alcohol drinking. International Journal of Cancer, 119, 4,
884–887 (2006).
[11] N.A. Ibrahim, A. Kudus, and I. Daud, Decision tree for competing risks survival
probability in breast cancer study. International Journal of Biomedical Sciences, 3,
1 (2008).
[12] T. Buchholz, Radiation therapy for early-stage breast cancer after breastconserving
surgery. The New England Journal of Medicine, 360, 1, 63-70 (2009).
[13] Y. Xu, J. Keper, and C.P. Tsokos, Identify attributable variables and interactions in
breast cancer. Journal of Applied Sciences, 11, 6, 1033-1038 (2011).

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