Streamlining a Transplantation Survival Prediction Program with a RDF Triplestore

Abstract

In this paper, we describe the conversion of a heart trans- plantation dataset in the RDF format and its application in a survival prediction program. The International Society for Heart & Lung Trans- plantation (ISHLT) maintains a registry of heart transplantations that it gathers from operations performed worldwide. The US United Net- work for Organ Sharing (UNOS) and the Scandinavian Scandiatrans- plant are contributors of this registry although they use different data models. We designed a unified graph representation covering the three data models and we converted the ISHLT tables into RDF triples. We used the resulting triplestore as input to a survival prediction program for transplanted patients [3, 2]. Recipient and donor properties are essen- tial to predict the mortality or survival of the patients. In contrast with the manual techniques we used to extract data from the tabulated files, the RDF triplestore enables us to experiment quickly and automatically with combinations of features that influence most the survival that we will demonstrate at the conference