Heart transplantation is lifesaving for patients with an end-stage heart disease. With an improved outcome prediction, we could be more confident in the post transplantation performance, and it would be possible to increase the survival as well as the number of organs that can be used. The plethora of medical databases that have been generated during the last two decades, which has opened up this entirely new field of opportunities for the development of advanced prediction models. Furthermore, the use of high-throughput genotyping technologies, we can now generate massive quantities of data, dense sets of genotypes from individual genomes, and complete genome sequences from multiple individuals. Analyzing this kind of non-linear data has led to increasing demands for advanced analysis methods and supercomputers.
- Associate Professor Johan Nilsson, MD, PhD. Dept of Clinical Sciences, Division of Cardiothoracic surgery, Lund University and Skåne University Hospital
- Associate Professor Pierre Nugues, PhD. Dept of Computer Science, LTH, Lund University
Web page: http://essenceofescience.se/aaot/