Building an Efficient Multi-stage Alzheimer’s Disease Classification System Using Computationally Effective Hybrid and Ensemble Models

Abstract Identifying Alzheimer’s disease stages accurately is crucial for timely detection and immediate and effective treatment regimens. Although existing Alzheimer’s stage classification achieved better performance, it was not conducted to achieve an accuracy-complexity trade-off. This research w...

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Detalles Bibliográficos

Principais autores:	Muppavarapu Chethan, P. Sabarinathan, R. Arumuga Arun, R. S. Rampriya, Rajkumar Soundrapandiyan
Formato:	Artigo
Idioma:	Inglês
Publicado:	Springer 2026-05-01
Series:	International Journal of Computational Intelligence Systems
Assuntos:	Alzheimer’s Disease Classification Computer Vision Hybrid Models Convolutional Neural Networks Lightweight Models Explainable AI
Acceso en liña:	https://doi.org/10.1007/s44196-026-01292-1
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