Keywords: Diagnosis/Prediction, Alzheimer's Disease
Motivation: Alzheimer's disease affects millions, but understanding its progression remains challenging. This study seeks to assess the severity of Alzheimer's from imaging data alone.
Goal(s): To create a score that reflects how far Alzheimer's has progressed in a patient.
Approach: Using brain scans and simple patient demographic information, we developed an imaging-based model that predicts the severity of Alzheimer's.
Results: Our model successfully distinguishes between different stages of Alzheimer's, offering a reliable disease progression score.
Impact: This work could lead to earlier detection and better tracking of Alzheimer's, informing treatment decisions and aiding in the objective development and evaluation of new therapies.
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