Big Data in the Clinical Neurosciences

G. Damian Brusko, Gregory Basil, Michael Y. Wang

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The clinical neurosciences have historically been at the forefront of innovation, often incorporating the newest research methods into practice. This chapter will explore the adoption, implementation, and refinement of big data and predictive modeling using machine learning within neurosurgery. Initial development of national databases arose from surgeons aiming to improve outcome predictions for patients with traumatic brain injury in the 1960s. In the following decades, other surgical specialties began building databases that left a lasting impact on the current national neurosurgical databases, particularly in spine surgery. Significant contributions to the literature have been made as a result of the numerous registries today, leading to broad quality improvements for neurosurgical patients. Important limitations of large databases do exist, including lack of standardized reporting and challenges in data extraction from medical records. New vistas will include the use of metadata to track human function, performance, and pain in a real-time manner to augment the reliance on traditional patient-reported outcome measures (PROMs). Overall, big data has demonstrated significant utility within neurosurgical research and machine learning-powered analyses have highlighted several promising areas of interest for future exploration.

Original languageEnglish (US)
Title of host publicationActa Neurochirurgica, Supplementum
PublisherSpringer Science and Business Media Deutschland GmbH
Pages271-276
Number of pages6
DOIs
StatePublished - 2022

Publication series

NameActa Neurochirurgica, Supplementum
Volume134
ISSN (Print)0065-1419
ISSN (Electronic)2197-8395

Keywords

  • Big Data
  • Database
  • Machine learning
  • National Registry
  • Neurosurgery
  • Patient-Reported Outcome Measures (PROMs)
  • Predictive analytics
  • Quality improvement

ASJC Scopus subject areas

  • Surgery
  • Clinical Neurology

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