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30th Anniversary AACR Special Conference
Convergence: Artificial Intelligence, Big Data and Prediction in Cancer
October 14-17, 2018
Newport, Rhode Island
Phillip A. Sharp, David H. Koch Institute for Integrative Cancer Research at MIT, Cambridge, Massachusetts
William C. Hahn, Dana-Farber Cancer Institute, Boston, Massachusetts
Judy E. Garber, Dana-Farber Cancer Institute, Boston, Massachusetts
Richard Klausner, Mindstrong Health, Palo Alto, California
Aviv Regev, Massachusetts Institute of Technology, Cambridge, Massachusetts
Charles L. Sawyers, Memorial Sloan Kettering Cancer Center, New York, New York
Information technologies have transformed many aspects of society but to date they have had a modest impact on diagnosis, prevention, or treatment of cancer. One of the first points of intersection of information technologies on advancing the understanding and control of cancer is the ability to predict the development, progression, and malignancy of the disease in both populations and individuals. New, transformative technologies are emerging that collect large sets of high-resolution data at levels of single molecules, single cells, specific tissues, organisms, and populations. Extracting insights from these big data sets requires development of new methods in information technologies and machine learning, and new concepts. It is this interface of cancer biology, computation, and clinical oncology that will most likely produce the future breakthroughs in control of cancer. This AACR Special Conference will cover the state of the art in understanding the disease of cancer from incident to early diagnosis, prevention, and treatment, with an emphasis on approaches that use big data and new computational methods such as machine learning. An important test of this understanding is whether it allows prediction of future outcomes.