Predictive Risk Analysis for Liver Transplant Patients — eHealth Model Under National Liver Transplant Program, Uruguay

Abstract

Recent years have seen a phenomenal change in healthcare paradigms and data analytics clubbed with computational intelligence has been a key player in this field. One of the main objectives of incorporating computational intelligence in healthcare analytics is to obtain better insights about the patients and proffer more efficient treatment. This work is based on liver transplant patients under the National Liver Transplant Program of Uruguay, considering in detail the health parameters of the patients. Applying computational intelligence helped to separate the cohort into clusters, thereby facilitating the efficient risk-group analysis of the patients assessed under the liver transplantation program with respect to their corresponding health parameters, in a predictive pre-transplant perspective. Also, this marks the foundation of Clinical Decision Support Systems in liver transplantation, which act as an assistive tool for the medical personnel in getting a deeper insight to patient health data and thanks to the holistic visualization of the healthcare scenario, also help in choosing a more efficient and personalized treatment strategy.