The Use of Deep Learning Software in the Detection of Voice Disorders: A Systematic Review.

Journal: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
PMID: 38168017

Abstract

OBJECTIVE: To summarize the use of deep learning in the detection of voice disorders using acoustic and laryngoscopic input, compare specific neural networks in terms of accuracy, and assess their effectiveness compared to expert clinical visual examination.

Authors

  • Joshua Barlow
    Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Zara Sragi
    Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Gabriel Rivera-Rivera
    Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Abdurrahman Al-Awady
    Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Ümit Daşdöğen
    Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Mark S Courey
    Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Diana N Kirke
    Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.

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