Survival model and estimation for lung cancer patients

Xingchen Yuan, Don Hong, Yu Shyr

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish
Title of host publicationQuantitative Medical Data Analysis Using Mathematical Tools and Statistical Techniques
PublisherWorld Scientific Publishing Co.
Pages201-219
Number of pages19
ISBN (Electronic)9789812772121
ISBN (Print)9812704612, 9789812704610
DOIs
Publication statusPublished - 2007 Jan 1

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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