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Machine learning strategies for the identification of language disorders in children
What is it about?
This review describes potential applications for artificial intelligence in the identification of language disorders in children. We highlight tools that can automatically extract linguistic features from rich language samples and identify language samples with developmental language disorder. We explain how certain tools work, and emphasize the advantages and challenges associated with these approaches regarding bias and feasibility.
Why is it important?
Advances in artificial intelligence call for an increased effort to understand how these tools can be used to make the diagnosis and treatment of language disorders more efficient and accessible. We identify the strengths of these approaches and areas for potential improvement, highlighting the importance of engaging clinicians in this process.