Alzheimer’s disease prediction algorithm based on hippocampal longitudinal hybrid morphological features | Synapse
March 3, 2026Open Access
Alzheimer’s disease prediction algorithm based on hippocampal longitudinal hybrid morphological features
Key Points
High accuracy demonstrated for predicting Alzheimer's disease using the prediction algorithm.
The proposed model effectively utilizes spatiotemporal correlation with hippocampal morphological features.
This analysis leverages longitudinal data to enhance prediction reliability, focusing on structural brain changes.
Implications highlight the potential for improved diagnostic approaches, particularly in early-stage interventions.
Abstract
These results highlight the effectiveness of the proposed model in leveraging the spatiotemporal correlation of hippocampal morphology to provide high accuracy and reliable predictions.