Combining neuroimaging data with artificial intelligence technology, researchers have identified a complex network within the brain that comprehends the meaning of spoken sentences.
The lessons learned from developing artificial intelligence networks can help guide researchers down the path of understanding the brain as a computational system rather than a collection of cells. AI technology can help take exploring the human brain, behavior and neurodegenerative diseases to an entirely new level.
Disruptions in fiber tracts connecting brain regions associated with cognitive behavior and emotional regulation in teens appear to be linked to higher risk of psychiatric disorders, researchers report.
When it comes to answering people's questions about cancer, especially regarding myths and misconceptions, ChatGPT is 97% accurate in providing the correct information. The AI is so accurate, test subjects were unaware whether the answers came from ChatGPT or the National Cancer Institute.
Findings allow for the development of an autonomously updating brain-machine interface, which is able to improve on its own by learning about its subject without additional programming. The system could help develop new robotic prosthetics, which can perform more naturally.
Researchers are developing a deep learning network capable of smelling human breath and identifying a range of illness revealing substances we may inhale.
A new artificial intelligence convolutional neural network is 94.6% accurate at diagnosing real-time intraoperative brain tumors.
Researchers reveal people are able to correctly identify, with 75% accuracy, expressions of emotion in others based on subtle changes in color around the nose, eyebrows and chin.
Using machine learning technology, researchers provide new insight into the neural mechanisms that govern anger and aggression.
Key biomarkers for predicting autism in newborns have been identified.
Researchers from UT Austin utilize deep learning and supercomputing to help identify brain tumors.
Combining artificial intelligence technology with data sets related to both Alzheimer's and COVID-19, researchers were able to identify a mechanism by which coronavirus can lead to Alzheimer's-like symptoms. The findings add to the growing body of evidence that COVID-19 infection can have lasting effects on brain function.
