Meta-Analysis of Voice Disorders Databases and Applied Machine Learning Techniques
Mathematical Biosciences and Engineering
Syed, S. A., Rashid, M., et al. (2020).
Mathematical Biosciences and Engineering, 17(6), 7958-7979.
This meta-analysis investigates the efficacy of different methods of machine learning used to identify voice disorders in individuals.
Not stated
Up to June 2020
Peer-reviewed studies of any design
45
This meta-analysis identified the overall accuracy of the Support Vector Machine (SVM) algorithm in detecting voice disorders using the following databases:<ul> <li>the Saarbruecken Voice Database (SVD) (71%-99.53%); </li> <li>the Massachusetts Eye and Ear Infirmary (MEEI) (87.06%-99.99%); and</li> <li>the Arabic Voice Pathology Database (AVPD) (72.53%-96.02%).</li></ul>The included studies focused on supervised techniques rather than unsupervised techniques. Additional research in this area is warranted.
