Machine learning helps determine which infants will gain the most from cochlear implantation

Intact hearing in early childhood is essential for normal development of communication skills and language. Neural circuits are responsible for the healthy development of hearing, which is foundational for most academic skills, such as reading and language communication. Deaf babies, or those born with impaired hearing abilities, may suffer from an ongoing deficit in communication skills and language development if they pass the time window critical for the development of these neural circuits along a typical trajectory. Indeed, about 3 out of every 1000 infants are born with severe or profound hearing loss (Cunningham and Cox, 2003), which is often caused by an impaired cochlear development (i.e. the auditory part of the inner ear). For many of these children, cochlear implantation at a very young age may be critical. However, there are some risks in a surgical procedure and parents may choose to delay a surgery to when the child is older. Therefore, it is critical to know which children will benefit and what age is ideal to have cochlear implantation, but how can we know which children will gain the most from this procedure? Recently, Tan and colleagues tackled this question by using a statistical technique called "machine learning" to predict which children will gain the best language skills within 2 years of implantation. How does machine learning work? This technique, as applied to neuroimaging data, commonly involves an algorithm that first has to "learn" how healthy ...
Source: Science - The Huffington Post - Category: Science Source Type: news