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Citations for "Assessment of Gastric Cancer Survival: Using an Artificial Hierarchical Neural Network"

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Aljawadi, B.A.I., M.R.A. Bakar, N.A. Ibrahim and H. Midi, 2011. Parametric estimation of the immunes proportion based on bch model and exponential distribution using left censored data. J. Applied Sci., 11: 2861-2865.
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Alkhasawneh, M.S., U.K. Bt Ngah, T.L. Tien and N.A.B. Mat Isa, 2012. Landslide susceptibility hazard mapping techniques review. J. Applied Sci., 12: 802-808.
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Biglarian, A., E. Hajizadeh and A. Kazemnejad, 2010. Comparison of artificial neural network and Cox regression models in survival prediction of gastric cancer patients. Koomesh, 11: 205-210.
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Jia-Sheng, L., W. Ying-De and T. Wang-Lan, 2013. Singular value detection of genetic algorithm optimizing RBF neural network. Inform. Technol. J., 12: 2201-2206.
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Development and validation of an artificial neural network prognostic model after gastrectomy for gastric carcinoma: An international multicenter cohort study
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Comparison between artificial neural network and Cox regression model in predicting the survival rate of gastric cancer patients
Biomedical Reports Vol. 1, Issue 5, 757, 2013

Parametric Estimation of the Immunes Proportion based on BCH Model and Exponential Distribution using Left Censored Data
Journal of Applied Sciences Vol. 11, Issue 15, 2861, 2011

Five Years Survival of Patients After Liver Transplantation and Its Effective Factors by Neural Network and Cox Poroportional Hazard Regression Models
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