Survival model and estimation for lung cancer patients

Lung cancer is the most frequently occuring fatal cancer in the United States. By assuming a form for the hazard function for a group of lung cancer patients for survival study, the covariates in the hazard function are estimated by the maximum likelihood estimation following the proportional hazards regression analysis. Although the proportional hazards model does not give an explicit baseline hazard function, the function can be estimated by fitting the data with non-linear least square technique. The survival model is then examined by a neural network simulation. The neural network learns the survival pattern from available hospital data and gives survival prediction for random covariate combinations. The simulation results support the covariate estimation in the survival model.