Effectiveness of FEES with artificial intelligence-assisted computer-aided diagnosis.

Journal: Auris, nasus, larynx
PMID: 37980257

Abstract

OBJECTIVES: FEES is a standard procedure for diagnosing dysphagia. However, appropriate evaluation of FEES findings is difficult for inexperienced evaluators. Recent progress in deep learning has highlighted the use of artificial intelligence-assisted computer-aided diagnosis (AI-assisted CAD) in medical applications. We investigated the detection accuracy of FEES findings evaluated by inexperienced evaluators with and without the use of CAD.

Authors

  • Mitsuyoshi Imaizumi
    Department of Otolaryngology, Fukushima Medical University School of Medicine, 1 Hikarigaoka, Fukushima 960-1295, Japan. Electronic address: ima-mitu@fmu.ac.jp.
  • Weihao Weng
    Graduate School of Computer Science and Engineering, The University of Aizu.
  • Xin Zhu
    Biomedical Information Engineering Lab, The University of Aizu, Fukushima, Japan.
  • Shigeyuki Murono
    Department of Otolaryngology, Fukushima Medical University School of Medicine, 1 Hikarigaoka, Fukushima 960-1295, Japan.

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