A Hybrid Deep Learning Framework to Predict Alzheimer’s Disease Progression Using Generative Adversarial Networks and Deep Convolutional Neural Networks

A major research subject in recent times is Alzheimer’s disease (AD) due to the growth and considerable societal impacts on health. So, the detection of AD is essential for medication care. Early detection of AD is critical for effective treatment, and monitoring the time period between normal aging...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Arabian journal for science and engineering (2011) Jg. 49; H. 3; S. 3267 - 3284
Hauptverfasser:	SinhaRoy, Rajarshi, Sen, Anupam
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024 Springer Nature B.V
Schlagworte:	Artificial neural networks Deep learning Engineering Generative adversarial networks Humanities and Social Sciences Machine learning Magnetic resonance imaging Medical imaging multidisciplinary Neural networks Research Article-Computer Engineering and Computer Science Science Healthcare Generative adversarial networks Alzheimer’s disease Convolutional neural networks Super-resolution GANs Deep convolutional GANs
ISSN:	2193-567X, 1319-8025, 2191-4281
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!