The Use of Deep Learning Software in the Detection of Voice Disorders: A Systematic Review.
Joshua BarlowZara SragiGabriel Rivera-RiveraAbdurrahman Al-AwadyÜmit DaşdöğenMark S CoureyDiana N KirkePublished in: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery (2024)
Deep learning models were shown to be highly accurate in the detection of voice pathology, with CNNs most effective for assessing laryngoscopy images and MLPs most effective for assessing acoustic input. While deep learning methods outperformed expert clinical exam in limited comparisons, further studies integrating external validation are necessary.