Assessing the Effect of Quantitative and Qualitative Predictors on Gastric Cancer Individuals Survival Using Hierarchical Artificial Neural Network Models | Zendy

Zohreh Amiri | Zendy; Kazem Mohammad | Zendy; Mahmood Mahmoudi | Zendy; Mahbubeh Parsaeian | Zendy; Hojjat Zeraati | Zendy

Open Access

Assessing the Effect of Quantitative and Qualitative Predictors on Gastric Cancer Individuals Survival Using Hierarchical Artificial Neural Network Models

Author(s) -

Zohreh Amiri,

Kazem Mohammad,

Mahmood Mahmoudi,

Mahbubeh Parsaeian,

Hojjat Zeraati

Publication year - 2013

Publication title -

iranian red crescent medical journal

Language(s) - English

Resource type - Journals

eISSN - 2074-1812

pISSN - 2074-1804

DOI - 10.5812/ircmj.4122

Subject(s) - proportional hazards model , artificial neural network , medicine , categorical variable , covariate , survival analysis , statistics , multinomial distribution , cancer , artificial intelligence , surgery , mathematics , computer science

There are numerous unanswered questions in the application of artificial neural network models for analysis of survival data. In most studies, independent variables have been studied as qualitative dichotomous variables, and results of using discrete and continuous quantitative, ordinal, or multinomial categorical predictive variables in these models are not well understood in comparison to conventional models.

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