Data supplementing the information found in "Inexpensive, Non-invasive Biomarkers Predict Alzheimer Transition using Machine Learning Analysis of the Alzheimer’s Disease Neuroimaging (ADNI) Database"
In this work we aimed to identify neural predictors of the efficacy of multimodal rehabilitative interventions in AD-continuum patients in the attempt to identify ideal candidates to improve the treat
This dataset represents a comprehensive resource for Alzheimer's Disease Polygenic Scores (AD PGSs) with enhanced annotations and aggregated rankings of genetic variants. This dataset is intended to f
Examine predictors of clinical and resource utilization outcomes associated with Alzheimer’s disease and related dementias (ADRD), stratified by patient severity profiles. Cross-sectional study of adu