A new AI model may signal a ‘paradigm shift’ in traumatic brain injury research by more accurately modeling the tissue deformations that lead to brain damage.
Stanford University researchers are leveraging artificial intelligence (AI) to help identify which computational models perform best at modeling mechanical stress on the brain, which may help drive insights into why some traumatic brain injuries (TBIs) lead to long-term brain damage while others do not.
The press release states that the ability to model the mechanical forces causing the compression, stretching, twisting, and other deformations of brain tissue that lead to brain damage is critical to understanding TBI. This modeling could help researchers understand why some TBIs lead to lasting brain damage and some don’t… Continue reading.
Some people may follow a football team, others may follow their favorite television streaming series. For Ellen Kuhl, PhD, a professor of mechanical engineering at Stanford, her passion lies in following proteins.
In a recent Stanford news article, Kuhl explains how her team developed a computer simulation to track the spread of defective proteins in the brain. These proteins contribute to the progression of neurodegenerative diseases such as Alzheimer’s, Parkinson’s, ALS and Lou Gehrig’s disease… Continue reading.