LAUSR

Overview As the drive towards precision medicine has accelerated, enabled by an ever-increasing abundance of new data and information, the opportunities and challenges in applying computational approaches in cancer research and clinical applications are also growing dramatically. The onset of exascale computing together with the rapid rise of deep learning as an enabling technology and its potential are reshaping the way computation is being applied across scales of computing, across time and across spatial scales. With legislation in the form of the Twenty-first Century Cures Act as well as efforts of the Beau Biden Cancer Moonshot, these underscore the importance of workshops that bring together interdisciplinary experts and insights across the spectrum of computational approaches for cancer. Several areas are highlighted as opportunities for innovation as disciplines converge in the interest of accelerating and extending the impact of computational approaches for cancer. As outlined in the 2016 Frontiers of Predictive Oncology and Computing meeting report, four distinct yet strongly inter-related areas of innovation include: