Artificial Intelligence Improves Novices' Bronchoscopy Performance: A Randomized Controlled Trial in a Simulated Setting.

Journal: Chest
PMID: 37619664

Abstract

BACKGROUND: Navigating through the bronchial tree and visualizing all bronchial segments is the initial step toward learning flexible bronchoscopy. A novel bronchial segment identification system based on artificial intelligence (AI) has been developed to help guide trainees toward more effective training.

Authors

  • Kristoffer Mazanti Cold
    Copenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, Copenhagen, University of Copenhagen and the Capital Region of Denmark; kristoffer.mazanti.cold.01@regionh.dk.
  • Sujun Xie
    Copenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, University of Copenhagen and the Capital Region of Denmark; Guangdong Academy for Medical Simulation (GAMS), Guangzhou, China.
  • Anne Orholm Nielsen
    Copenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, Copenhagen, University of Copenhagen and the Capital Region of Denmark; Department of Pulmonary Medicine, Bispebjerg Hospital.
  • Paul Frost Clementsen
    Copenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, Copenhagen, University of Copenhagen and the Capital Region of Denmark.
  • Lars Konge
    Copenhagen Academy for Medical Education and Simulation (CAMES), Copenhagen, Denmark.

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