Can Artificial Intelligence Mitigate Missed Diagnoses by Generating Differential Diagnoses for Neurosurgeons?

Journal: World neurosurgery
PMID: 38759788

Abstract

BACKGROUND/OBJECTIVE: Neurosurgery emphasizes the criticality of accurate differential diagnoses, with diagnostic delays posing significant health and economic challenges. As large language models (LLMs) emerge as transformative tools in healthcare, this study seeks to elucidate their role in assisting neurosurgeons with the differential diagnosis process, especially during preliminary consultations.

Authors

  • Rohit Prem Kumar
    Department of Neurological Surgery, University of Pittsburgh School of Medicine, UPMC Presbyterian, Suite B-400, 200 Lothrop Street, Pittsburgh, PA 15213, USA.
  • Vijay Sivan
    Department of Neurosurgery, Hackensack Meridian School of Medicine, Nutley, New Jersey, USA.
  • Hanin Bachir
    Department of Neurosurgery, Hackensack Meridian School of Medicine, Nutley, New Jersey, USA.
  • Syed A Sarwar
    Department of Neurosurgery, Hackensack Meridian School of Medicine, Nutley, New Jersey, USA.
  • Francis Ruzicka
    Department of Neurosurgery, Hackensack Meridian School of Medicine, Nutley, New Jersey, USA.
  • Geoffrey R O'Malley
    Department of Neurosurgery, Hackensack Meridian School of Medicine, Nutley, New Jersey, USA.
  • Paulo Lobo
    Department of Neurosurgery, Hackensack Meridian School of Medicine, Nutley, New Jersey, USA.
  • Ilona Cazorla Morales
    Department of Neurosurgery, Hackensack Meridian School of Medicine, Nutley, New Jersey, USA.
  • Nicholas D Cassimatis
    Department of Neurosurgery, Hackensack Meridian School of Medicine, Nutley, New Jersey, USA.
  • Jasdeep S Hundal
    Department of Neurology, HMH-Jersey Shore University Medical Center, Neptune, New Jersey, USA.
  • Nitesh V Patel
    Department of Neurosurgery, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey.

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