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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Hauptverfasser:	Muppavarapu Chethan, P. Sabarinathan, R. Arumuga Arun, R. S. Rampriya, Rajkumar Soundrapandiyan
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Springer 2026-05-01
Schriftenreihe:	International Journal of Computational Intelligence Systems
Schlagworte:	Alzheimer’s Disease Classification Computer Vision Hybrid Models Convolutional Neural Networks Lightweight Models Explainable AI
Online-Zugang:	https://doi.org/10.1007/s44196-026-01292-1
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