Researchers have developed a method to assess Alzheimer’s disease severity by analyzing patterns of tau pathology in brain scans. Using unsupervised machine learning, they identified eight patterns of tau deposition correlated with clinical outcomes. This model could help determine disease progression and guide treatment decisions. The study, published in Alzheimer’s and Dementia, aims to monitor tau pathology and create a model for future patients to intervene earlier and slow cognitive decline in Alzheimer’s. This innovative approach could provide valuable insights into the progression of the disease and potentially improve patient outcomes.
Source link
New method uses tau protein deposition patterns to predict Alzheimer’s severity
