A Novel Approach to the Prediction of Alzheimer’s Disease Progression by Leveraging Neural Processes and a Transformer Encoder Model

A Novel Approach to the Prediction of Alzheimer’s Disease Progression by Leveraging Neural Processes and a Transformer Encoder Model

Alzheimer’s disease (AD) presents a significant global health challenge, necessitating accurate and early prediction methods for effective intervention and treatment planning. In this work, a novel approach to meta-learning for the prediction of AD is proposed, which leverages the combine...

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Bibliographic Details
Main Authors: Emad Al-Anbari, Hossein Karshenas, Bijan Shoushtarian
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Alzheimer’s disease
disease progression modeling
neural processes
Bayesian analysis
transformer
Online Access:https://ieeexplore.ieee.org/document/10910173/
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https://ieeexplore.ieee.org/document/10910173/

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