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

• Published in: Arabian journal for science and engineering (2011) Vol. 49; no. 3; pp. 3267 - 3284
• Main Authors: SinhaRoy, Rajarshi, Sen, Anupam
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024; Springer Nature B.V
• Subjects: 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

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...