Scoping review of deep learning research illuminates artificial intelligence chasm in otolaryngology-head and neck surgery.

Journal: NPJ digital medicine
Published Date: May 10, 2025

Abstract

Clinical validation studies are important to translate artificial intelligence (AI) technology in healthcare but may be underperformed in Otolaryngology - Head & Neck Surgery (OHNS). This scoping review examined deep learning publications in OHNS between 1996 and 2023. Searches on MEDLINE, EMBASE, and Web of Science databases identified 3236 articles of which 444 met inclusion criteria. Publications increased exponentially from 2012-2022 across 48 countries and were most concentrated in otology and neurotology (28%), most targeted extending health care provider capabilities (56%), and most used image input data (55%) and convolutional neural network models (63%). Strikingly, nearly all studies (99.3%) were in silico, proof of concept early-stage studies. Three (0.7%) studies conducted offline validation and zero (0%) clinical validation, illuminating the "AI chasm" in OHNS. Recommendations to cross this chasm include focusing on low complexity and low risk tasks, adhering to reporting guidelines, and prioritizing clinical translation studies.

Authors

  • George S Liu
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA. gliu51@jh.edu.
  • Soraya Fereydooni
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Melissa Chaehyun Lee
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Srinidhi Polkampally
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Jeffrey Huynh
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Sravya Kuchibhotla
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Mihir M Shah
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Noel F Ayoub
    Division of Rhinology and Skull Base Surgery, Department of Otolaryngology--Head & Neck Surgery, Mass Eye and Ear/Harvard Medical School, Boston, MA.
  • Robson Capasso
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Michael T Chang
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Philip C Doyle
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • F Christopher Holsinger
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Zara M Patel
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Jon-Paul Pepper
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • C Kwang Sung
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Francis X Creighton
    Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University, Baltimore, MD, USA.
  • Nikolas H Blevins
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.
  • Konstantina M Stankovic
    Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA, USA.

Keywords

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