A Deep Learning Approach for Automated Diagnosis and Multi-Class Classification of Alzheimer’s Disease Stages Using Resting-State fMRI and Residual Neural Networks

• Published in: Journal of medical systems Vol. 44; no. 2; p. 37
• Main Authors: Ramzan, Farheen, Khan, Muhammad Usman Ghani, Rehmat, Asim, Iqbal, Sajid, Saba, Tanzila, Rehman, Amjad, Mehmood, Zahid
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2020; Springer Nature B.V
• Subjects: Alzheimer's disease; Artificial neural networks; Classification; Deep learning; Dementia disorders; Functional magnetic resonance imaging; Health Informatics; Health Sciences; Image & Signal Processing; Machine learning; Medical diagnosis; Medical imaging; Medicine; Medicine & Public Health; Neural networks; Neurodegenerative diseases; NMR; Nuclear magnetic resonance; Resonance; Statistics for Life Sciences; Deep learning; Alzheimer’s disease; Classification; Functional magnetic resonance imaging (fMRI); Diagnosis; Multi-class; Residual neural networks

Alzheimer’s disease (AD) is an incurable neurodegenerative disorder accounting for 70%–80% dementia cases worldwide. Although, research on AD has increased in recent years, however, the complexity associated with brain structure and functions makes the early diagnosis of this disease a challenging t...