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Personalized Model Unveils Hidden Patterns in Alzheimer s Progression | Duke University School of Medicine

A new mathematical model offers hope for better prediction and treatment of Alzheimer’s disease.  Most mathematical models of Alzheimer’s are theoretical, focusing on short term molecular and cellular-level changes that cannot be measured in patients. However, researchers at Duke University School of Medicine and Pennsylvania State University have used real-world data from over 800 people with varying cognitive abilities, to develop the Alzheimer’s Disease Biomarker Cascade (ADBC) model.  

Computational model uses biomarkers to predict Alzheimer s progression

Computational model uses biomarkers to predict Alzheimer s progression
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