Bayesian Classifier and Molecular Marker Platforms for Immune Monitoring

Machine learning has been used in health care for over a decade. For example, models developed through this approach have been used in oncology to predict response to treatment based on tumor biomarker profiles. Machine learning is used in transplantation to elucidate biomarkers involved in the development of transplant glomerulopathy (TG), as a tool for deceased donor kidney allocation, and to increase the understanding of how beliefs within minority populations influence organ donation. In this chapter, these approaches are discussed in their current evolution and future directions with a focus on Bayesian belief networks (BBNs) and monitoring of immune status across transplantation.