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

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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
Pages (from-to)E793-E810
Number of pages18
JournalMedical Physics
Volume45
Issue number10
DOIs
Publication statusPublished - Oct 2018

Keywords

  • big data
  • ontology
  • standardization
  • informatics
  • machine learning
  • RADIOTHERAPY RESEARCH
  • CANCER-PATIENTS
  • THERAPY
  • INFORMATION
  • POPULATION
  • DATABASES
  • MEDICINE

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