The Effectiveness of Supervised Machine Learning in Screening and Diagnosing Voice Disorders: Systematic Review and Meta-analysis.

ABSTRACT:

Background

When investigating voice disorders a series of processes are used when including voice screening and diagnosis. Both methods have limited standardized tests, which are affected by the clinician's experience and subjective judgment. Machine learning (ML) algorithms have been used as an objective tool in screening or diagnosing voice disorders. However, the effectiveness of ML algorithms in assessing and diagnosing voice disorders has not received sufficient scholarly attention.

Objective

This systematic review aimed to assess the effectiveness of ML algorithms in screening and diagnosing voice disorders.

Methods

An electronic search was conducted in 5 databases. Studies that examined the performance (accuracy, sensitivity, and specificity) of any ML algorith

SUBMITTER: Al-Hussain G 

PROVIDER: S-EPMC9617188 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature