Promises and Perils of Artificial Intelligence in Neurosurgery

Sandip S. Panesar, Michel Kliot, Rob Parrish, Juan Fernandez-Miranda, Yvonne Cagle, Gavin W. Britz

Research output: Contribution to journalReview articlepeer-review

43 Scopus citations

Abstract

Artificial intelligence (AI)-facilitated clinical automation is expected to become increasingly prevalent in the near future. AI techniques may permit rapid and detailed analysis of the large quantities of clinical data generated in modern healthcare settings, at a level that is otherwise impossible by humans. Subsequently, AI may enhance clinical practice by pushing the limits of diagnostics, clinical decision making, and prognostication. Moreover, if combined with surgical robotics and other surgical adjuncts such as image guidance, AI may find its way into the operating room and permit more accurate interventions, with fewer errors. Despite the considerable hype surrounding the impending medical AI revolution, little has been written about potential downsides to increasing clinical automation. These may include both direct and indirect consequences. Directly, faulty, inadequately trained, or poorly understood algorithms may produce erroneous results, which may have wide-scale impact. Indirectly, increasing use of automation may exacerbate de-skilling of human physicians due to over-reliance, poor understanding, overconfidence, and lack of necessary vigilance of an automated clinical workflow. Many of these negative phenomena have already been witnessed in other industries that have already undergone, or are undergoing "automation revolutions," namely commercial aviation and the automotive industry. This narrative review explores the potential benefits and consequences of the anticipated medical AI revolution from a neurosurgical perspective.

Original languageEnglish (US)
Pages (from-to)33-44
Number of pages12
JournalNeurosurgery
Volume87
Issue number1
DOIs
StatePublished - Jul 1 2020

Keywords

  • Artificial intelligence
  • Automation
  • Deep learning
  • Diagnostics
  • Machine learning
  • Prognostication
  • Surgical adjuncts
  • Artificial Intelligence/trends
  • Algorithms
  • Humans
  • Neurosurgery/methods
  • Neurosurgical Procedures/methods

ASJC Scopus subject areas

  • Medicine(all)

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