Data and Artificial Intelligence (AI) are a match seemingly made in heaven. By joining data and AI, scientists are able to shift a lot of the burden associated with using data from human to machine. See why the data-AI relationship works so well for cancer research in this offbeat blog featuring two fictitious characters—Datum and his pal Aida.
CBIIT’s NIH Data and Technology Advancement (DATA) Scholar, Dr. Jay G. Ronquillo, offers a bird’s-eye view of cloud computing, including tips for managing costs, access, and training to help advance precision medicine and cancer research.
Converting the many petabytes of cancer data available on the cloud from information to answers is a complex task. In this blog, Deena Bleich shares how the ISB Cancer Gateway in the Cloud (ISB-CGC), an NCI Cloud Resource, hosts large quantities of cancer data in easily accessible Google BigQuery tables, expediting the process.
Allen Dearry, Ph.D., will retire from NCI’s CBIIT on December 31. Here Dr. Dearry reflects on his 31 years at NIH, including his role in helping to establish the Cancer Research Data Commons. He also offers advice for people just entering the field and describes what he’s planning to do next.
In this latest Data Science Seminar, Jim Lacey, Ph.D., M.P.H., shares the lessons he learned in transitioning a large cancer epidemiology cohort study to the cloud, including the importance of focusing on people and processes as well as technology. Project managers, principal investigators, co-investigators, data managers, data analysts—really anyone who is part of a team that wants to use the cloud or cloud-based resources for their studies—should attend.