Big Data and the Future of Radiology Informatics

Akash P. Kansagra, John Paul J. Yu, Arindam R. Chatterjee, Leon Lenchik, Daniel S. Chow, Adam B. Prater, Jean Yeh, Ankur M. Doshi, C. Matthew Hawkins, Marta E. Heilbrun, Stacy E. Smith, Martin Oselkin, Pushpender Gupta, Sayed Ali

Research output: Contribution to journalArticlepeer-review

61 Scopus citations


Rapid growth in the amount of data that is electronically recorded as part of routine clinical operations has generated great interest in the use of Big Data methodologies to address clinical and research questions. These methods can efficiently analyze and deliver insights from high-volume, high-variety, and high-growth rate datasets generated across the continuum of care, thereby forgoing the time, cost, and effort of more focused and controlled hypothesis-driven research. By virtue of an existing robust information technology infrastructure and years of archived digital data, radiology departments are particularly well positioned to take advantage of emerging Big Data techniques. In this review, we describe four areas in which Big Data is poised to have an immediate impact on radiology practice, research, and operations. In addition, we provide an overview of the Big Data adoption cycle and describe how academic radiology departments can promote Big Data development.

Original languageEnglish
Pages (from-to)30-42
Number of pages13
JournalAcademic radiology
Issue number1
StatePublished - Jan 1 2016


  • Informatics
  • Personalized medicine
  • Radiology
  • Value
  • Workflow


Dive into the research topics of 'Big Data and the Future of Radiology Informatics'. Together they form a unique fingerprint.

Cite this