Treatment data and technical process challenges for practical big data efforts in radiation oncology

C. S. Mayo, M. Phillips, T. R. McNutt, J. Palta, A. Dekker, R. C. Miller, Y. Xiao, J. M. Moran, M. M. Matuszak, P. Gabriel, A. S. Ayan, J. Prisciandaro, M. Thor, N. Dixit, R. Popple, J. Killoran, E. Kaleba, M. Kantor, D. Ruan, R. KapoorM. L. Kessler, T. S. Lawrence

Research output: Contribution to journalArticlepeer-review

Abstract

The term Big Data has come to encompass a number of concepts and uses within medicine. This paper lays out the relevance and application of large collections of data in the radiation oncology community. We describe the potential importance and uses in clinical practice. The important concepts are then described and how they have been or could be implemented are discussed. Impediments to progress in the collection and use of sufficient quantities of data are also described. Finally, recommendations for how the community can move forward to achieve the potential of big data in radiation oncology are provided.

Original languageEnglish (US)
Pages (from-to)e793-e810
JournalMedical physics
Volume45
Issue number10
DOIs
StatePublished - Oct 2018

Keywords

  • big data
  • informatics
  • machine learning
  • ontology
  • standardization

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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