As the drive towards precision medicine has accelerated, the opportunities
and challenges in using computational approaches in cancer research and
clinical application are rapidly growing. The rapid rise of deep learning as an
enabling technology and its potential are reshaping the way computation is
being applied across scales scales of computing, across time and across spatial
scales. With recent legislation in the form of the Twenty-first Century Cures
Act as well as efforts of the Beau Biden Cancer Moonshot all underscore the
importance of a workshop that brings together experts and insights across the
spectrum of computational approaches for cancer.
In the workshop, we bring together the computational community exploring and using high-performance computing, analytics, predictive modeling, and large datasets in cancer research and clinical applications. The workshop is inherently inter-disciplinary, with the common interest in cancer and computation the unifying theme. As such, the workshop provides rich opportunities for attendees to learn about future directions, current applications and challenges and build collaborations. Maintaining a perspective of accelerating scientific insights and translation of insights to clinical application for improved patient outcomes, the workshop brings together many interests from across the technology, cancer research and clinical domains.
The target audience for the workshop is those with shared interests in computational approaches for cancer. The workshop is again expected to attract those developers, researchers, and vendors with technologies and solutions believed to hold potential to address problems in cancer and seeking potential collaborators to work with. The workshop will also attract cancer investigators, clinicians and others who have recognized the need for HPC solutions, seeking an overview of potential solutions and potential collaborators. The third segment of the target audience are those individuals seeking career opportunities in cancer research and/or clinical applications, where the workshop will highlight forward looking directions in these areas.
This year’s program will continue to provide the broad-base community
interaction critical to the interdisciplinary advances needed to accelerate
cancer research and clinical applications. With a rapidly evolving field, the
session will survey exiting new developments in computational approaches for
cancer, selected from emerging topics of interest.
In addition, this year’s program will include a special session on Machine Learning Applied to Cancer – highlighting advances and paper submissions from the HPC and cancer research community.
The CAFCW workshop annually identifies a special workshop focus of significant interest to the community, bringing a special emphasis to the workshop for the year. The use of machine learning in multiple contexts (AI, cognitive learning, deep learning, etc.) has dramatically accelerated in the cancer research and clinical space. This has led to several innovations and rapid development of new techniques, while highlighting key challenges to overcome in order to more fully utilize these technologies.