Large Language Models-Supported Thrombectomy Decision-Making in Acute Ischemic Stroke Based on Radiology Reports: Feasibility Qualitative Study.

Journal: Journal of medical Internet research
PMID: 39946168

Abstract

BACKGROUND: The latest advancement of artificial intelligence (AI) is generative pretrained transformer large language models (LLMs). They have been trained on massive amounts of text, enabling humanlike and semantical responses to text-based inputs and requests. Foreshadowing numerous possible applications in various fields, the potential of such tools for medical data integration and clinical decision-making is not yet clear.

Authors

  • Jonathan Kottlors
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Robert Hahnfeldt
    Department of Diagnostic and Interventional Radiology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
  • Lukas Görtz
    Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Andra-Iza Iuga
    Institute for Diagnostic and Interventional Radiology, University Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Straße 62, 50937, Cologne, Germany. Electronic address: andra.iuga@uk-koeln.de.
  • Philipp Fervers
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Johannes Bremm
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • David Zopfs
    Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
  • Kai R Laukamp
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Oezguer A Onur
    From the Department of Neurology (H.G., M.H.T.S., C.W., J.D., N.R., G.R.F., O.A.O.), Faculty of Medicine and University Hospital Cologne; Division of Cardiology, Pneumology, Angiology and Intensive Care (C.A., S. Baldus), Department of Internal Medicine III, University of Cologne; Department of Neurology (S. Bittner), University Medical Center Mainz; Cognitive Neuroscience (N.R., O.A.O.), Institute of Neuroscience and Medicine (INM-3), Research Center Jülich; and Institute for Diagnostic and Interventional Radiology (C.Z., C.G., M.S.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany.
  • Simon Lennartz
    Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
  • Michael Schönfeld
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • David Maintz
    Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
  • Christoph Kabbasch
  • Thorsten Persigehl
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Marc Schlamann
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.

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