AI Model Tracks Brain Aging to Predict Cognitive Decline Risk
A newly developed AI tool uses MRI scans to measure brain aging speed, offering potential for early detection of Alzheimer’s and other neurodegenerative conditions.
- Researchers at USC have created a 3D convolutional neural network (3D-CNN) that measures the pace of brain aging using longitudinal MRI scans.
- The model identifies faster brain aging as a strong indicator of cognitive decline, including memory loss and reduced processing speed.
- Unlike traditional methods, this tool tracks brain changes over time and highlights specific regions most impacted by aging.
- The AI could help identify individuals at higher risk for Alzheimer’s disease before symptoms appear, enabling earlier intervention and personalized treatment strategies.
- The study also explores how genetics, environment, and lifestyle factors influence brain aging, with potential applications in tailoring preventative care.
Neuroscience News 
GEN 