Objectives: A systematic review of the literature was undertaken (1) to investigate research trends on how artificial intelligence is being used for assessment and diagnosis in the field of communication disorders and (2) to suggest consideration and a directions for the effective use of artificial intelligence in clinical settings. Methods: A total of 328 articles published in foreign journals between January 2016 and August 2021 were searched using 6 databases and a manual search, and 18 articles were finally selected according to PICO strategy (Population, Intervention, Comparison, Outcome) inclusion and exclusion criteria. Four authors determined the report selection and data extraction. They also independently analyzed the quality of the selected papers using QUADAS-II (Quality Assessment of Diagnostic Accuracy Studies-II). Results: Firstly, the selected studies had a generally low risk of bias. Secondly, the major subjects of studies were children with communication disorders. Thirdly, most of the studies included in the analysis were experimental studies to verify the effectiveness of using artificial intelligence. Lastly, the extracted features for assessment and diagnosis were biased against acoustic features at the levels of phoneme and word in speaking tasks. The performance of artificial intelligence in the selected studies differed according to the research purpose and evaluation metrics.
|Translated title of the contribution||Applications and Performances of Artificial Intelligence in Assessment and Diagnosis of Communication Disorders: A Systematic Review of the Literatures|
|Number of pages||20|
|Journal||Communication Sciences and Disorders|
|State||Published - 2022|
Bibliographical noteFunding Information:
This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2021-0-00406, Development of language therapy platform for children with language development delays and disabilities).
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A3A2A01096102).
© 2022 Korean Academy of Speech-Language Pathology and Audiology
- Artificial intelligence (ai)
- Assessment and diagnosis
- Communication disorders
- Convergence research
- Deep learning
- Machine learning