Author : Nitin D. Thorve and Dr. Pankaj Agarkar

Prediction            of            long-term            survival after      Liver Transplantation (LT) is one of the most difficult area in the field of medicine. The final treatment for the last stage of liver disease is liver transplantation. Going to any transplant, everyone will think about survival. This paper summarizes the prognosis of survival of patients who have undergone liver transplantation, both in computing and in clinical terms. The system proposed a cloudbased hybrid classifier with Artificial neural network (ANN) model to address the problem of organ allocation as well as survival prediction using a United Nations for Organ Sharing (UNOS) dataset. The (UNOS) dataset contains 389 attributes, and of these 389, 256 attributes are related to liver transplantation patients, form this 256 only 70 attributes consist of donor attributes, transplant attributes, and recipient attributes, and of these 70, only 28 attributes are used in our proposed system. This model extracts the corresponding attributes using Principal component analysis (PCA) algorithm and classifies the data set into training and test sets by using hybrid classifier. The relationship between attributes has been recognized and proven by various methods of Association rule analysis, such as Apriori algorithms. The corresponding donor-recipient pairs were selected using ten-fold cross-validation (CV) in the training of medical data. The proposed efficient and accurate artificial neural network (ANN) model predicts the long-term survival of liver patients who undergo Liver transplantation (LT), and then the predicted data is uploaded to the Amazon Web Services (AWS) cloud.  Finally, proposed Hybrid Classifier (MLP+LM) accuracy is compared with existing Multi-layer Perceptron (MLP), Recurrent Neural Network (RNN) algorithm.

Keywords: Liver Transplantation (LT), Cloud based Hybrid classifier, Artificial neural network (ANN), ten-fold crossvalidation (CV), Multi-layer Perceptron (MLP), Amazon Web Services (AWS) cloud