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Researchers at Northwestern University developed a new AI model that can predict how well children with severe hearing loss will develop spoken language after receiving cochlear implants. The study analyzed brain MRI scans taken before surgery from 278 children across the United States, Australia, and Hong Kong. Using deep transfer learning, a form of machine learning that adapts knowledge from large datasets, the model predicted language outcomes more accurately than traditional approaches.
The AI model achieved about 92 percent accuracy in forecasting whether a child would experience strong or limited improvement in spoken language one to three years after implantation. Researchers say the tool helps doctors identify children who may need more intensive speech and language therapy early on, allowing for more personalized care and better long-term outcomes.
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