Voice disorders classification using machine learning: a scoping review - Takeaways - MDSpire

Voice disorders classification using machine learning: a scoping review

  • By

  • Rijul Gupta

  • Craig T. Jin

  • Dhanshree R. Gunjawate

  • Duy Duong Nguyen

  • Brian Stasak

  • Antonia M. Chacon

  • Catherine Madill

  • June 8, 2026

  • 0 min

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  • 1

    This scoping review identifies barriers to the clinical application of machine learning in multi-class voice disorder classification.

  • 2

    A total of 80 articles utilizing machine learning for multi-class voice disorder classification were analyzed, revealing significant inconsistencies.

  • 3

    Variations in diagnostic labels, data availability, and testing methodologies hinder comparability and generalization of machine learning models.

  • 4

    The lack of consensus on classification frameworks among clinicians contributes to challenges in the automated classification of voice disorders.

  • 5

    Addressing identified barriers is essential for realizing the potential of voice as a biomarker for systemic diseases.

Original Source(s)

Voice disorders classification using machine learning: a scoping review

  • by Rijul Gupta, Craig T. Jin, Dhanshree R. Gunjawate, Duy Duong Nguyen, Brian Stasak, Antonia M. Chacon, Catherine Madill

  • June 8, 2026

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