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Investigating the Role of Artificial Intelligence in Predicting Perceived Dysphonia Level Publisher Pubmed



Saeedi S1 ; Aghajanzadeh M2
Authors
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Authors Affiliations
  1. 1. Independent Researcher in Laryngology, Voice Pathology, and Speech-Language Pathology, Tehran, Iran
  2. 2. Department of Speech Therapy, School of Rehabilitation, Tehran University of Medical Sciences, Enghelab Avenue, Pitch-e-Shemiran, Tehran, 11489, Iran

Source: European Archives of Oto-Rhino-Laryngology Published:2024


Abstract

Purpose: This study aims to investigate the role of one of these models in the field of voice pathology and compare its performance in distinguishing the perceived dysphonia level. Methods: Demographic information, voice self-assessments, and acoustic measurements related to a sample of 50 adult dysphonic outpatients were presented to ChatGPT and Perplexity AI chatbots, which were interrogated for the perceived dysphonia level. Results: The agreement between the auditory-perceptual assessment by experts and ChatGPT and Perplexity AI chatbots, as determined by Cohen’s Kappa, was not statistically significant (p = 0.429). There was also a low positive correlation (rs = 0.30, p = 0.03) between the diagnosis made by ChatGPT and Perplexity AI chatbots (rs = 0.30, p = 0.03). Conclusion: It seems that AI could not play a vital role in helping the voice care teams determine the perceptual level of dysphonia. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
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