Alz-SAENet: A Deep Sparse Autoencoder based Model for Alzheimer’s Classification

Precise identification of Alzheimer's Disease (AD) is vital in health care, especially at an early stage, since recognizing the likelihood of incidence and progression allows patients to adopt preventive measures before irreparable brain damage occurs. Magnetic Resonance Imaging is an effective...

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Veröffentlicht in:	International journal of advanced computer science & applications Jg. 13; H. 10
Hauptverfasser:	Reddy, G Nagarjuna, Reddy, K Nagi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	West Yorkshire Science and Information (SAI) Organization Limited 2022
Schlagworte:	Alzheimer's disease Artificial neural networks Brain damage Extraction procedures Feature extraction Magnetic resonance imaging Neural networks
ISSN:	2158-107X, 2156-5570
Online-Zugang:	Volltext
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