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| Models discovered by the Constitutive Artificial Neural Network outperform existing models for brain tissue. Image Credit: Ellen Kuhl |
By helping researchers choose among thousands of available computational models of mechanical stress on the brain, AI is yielding powerful new insight on traumatic brain injury.
From the gridiron to the battlefield, the study of traumatic brain injury has exploded in recent years. Crucial to understanding brain injury is the ability to model the mechanical forces that compress, stretch, and twist the brain tissue and cause damage that ranges from fleeting to fatal.
Researchers at Stanford University now say they have tapped artificial intelligence to produce a profoundly more accurate model of how deformations translate into stresses in the brain and believe that their approach could reveal a more definitive understanding of when and why concussion sometimes leads to lasting brain damage, and other times not.
“The problem in brain modeling to date is that the brain is not a homogeneous tissue – it’s not the same in every part of the brain. Yet, trauma is often pervasive,” said Ellen Kuhl, professor of mechanical engineering, director of the Living Matter Lab, and senior author of a new study appearing in the journal, Acta Biomaterialia. “The brain is also ultrasoft, much like Jell-O, which makes both testing and modeling physical effects on the brain very challenging.”
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