Scientists have proposed a method for predicting the level of intelligence of children using brain MRI using three-dimensional deep learning networks.
Magnetic resonance imaging isA common way to capture images of internal organs. The researchers decided to study the possibility of using the brain images thus obtained to determine the biological intellectual potential of adolescents, regardless of knowledge, age and gender.
To do this, a team from Skoltech created a three-dimensional neural architecturenetwork which to increase the accuracy of the forecastapplied several mathematical models to the same data at once. For the analysis of MRI using machine vision, a new ensemble method was used, which allows you to classify images entirely and without loss of information.
The study found a correlationbetween the level of “fluid” the child's intelligence and the anatomy of his brain. Although the prediction accuracy is still below the desired level, the developed models open up new aspects of child development.
Machine learning technologies also allowidentify signs of illness in children that even doctors may not pay attention to. For example, researchers recently developed a phone app that analyzes photographs to look for early signs of eye disease.
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