Amyloid-β Prediction Machine Learning Model Using Source-based Morphometry Across Neurocognitive Disorders

This article discusses the development of a machine learning model for predicting Alzheimer’s disease using source-based morphometry and a data-driven algorithm. The model was found to have high accuracy and was able to correctly detect Aβ-positivity in non-AD patients. The study also assessed the impact of different features on the model’s accuracy.