Application of statistical models for liver disease patients.

      Аннотация: Cirrhosis and HC are increasing causes of morbidity and mortality in developing countries, being the 14th most common cause of death worldwide. The present research work is an effort on the estimation of survival time and identification of prognostic factors of advance liver disease patients using various statistical techniques. This will help to device new strategies which will help in prevention and early intervention to stabilize disease progression and to avoid the need for liver transplantation. The challenge in the 21st century is to prevent the need for liver transplantation in as many patients suffering from liver disease as possible.

Ключевые слова: Cirrhosis, Cox proportional hazard model, Frailty Models, HCC, Markov models, AFT Models