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A new study found that an artificial intelligence model could forecast how effective a cochlear implant will be at improving a child’s speech, based on available data pre-operation. Researchers trained a deep learning system on brain scans and other pre-implant information from hundreds of children with severe hearing loss, and the model was able to predict spoken language outcomes with 92 percent accuracy, even across different languages and clinical sites. This approach can help identify which children might need more intensive speech and language support early on, giving clinicians a way to tailor therapies before the implant is activated.
The tool is another move beyond traditional prediction methods that rely mainly on age and residual hearing, which often don’t capture individual variability in speech progress after implantation. By using an AI to predict to prescribe, clinicians might be able to offer highly customized intervention plans that lead to better long-term language development for kids receiving cochlear implants.
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