Big Data Defined: A Practical Review for Neurosurgeons

Mohamad Bydon, Clemens M. Schirmer, Eric K. Oermann, Ryan S. Kitagawa, Nader Pouratian, Jason Davies, Ashwini Sharan, Lola B. Chambless

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Background: Modern science and healthcare generate vast amounts of data, and, coupled with the increasingly inexpensive and accessible computing, a tremendous opportunity exists to use these data to improve care. A better understanding of data science and its relationship to neurosurgical practice will be increasingly important as we transition into this modern “big data” era. Methods: A review of the literature was performed for key articles referencing big data for neurosurgical care or related topics. Results: In the present report, we first defined the nature and scope of data science from a technical perspective. We then discussed its relationship to the modern neurosurgical practice, highlighting key references, which might form a useful introductory reading list. Conclusions: Numerous challenges exist going forward; however, organized neurosurgery has an important role in fostering and facilitating these efforts to merge data science with neurosurgical practice.

Original languageEnglish (US)
Pages (from-to)e842-e849
JournalWorld neurosurgery
StatePublished - Jan 2020
Externally publishedYes


  • Clinical practice
  • Data science
  • Machine learning
  • Registry

ASJC Scopus subject areas

  • Surgery
  • Clinical Neurology


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