A Deep Learning Approach for Automated Diagnosis and Multi-Class Classification of Alzheimer’s Disease Stages Using Resting-State fMRI and Residual Neural Networks
By Farheen Ramzan, Muhammad Usman Ghani Khan, Muhammad Asim Rehmat, Sajid Iqbal, Tanzila Saba, Amjad Rehman, Zahid Mehmood. Journal of medical systems, 2019
357 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Neurology
View Paper: https://www.semanticscholar.org/paper/677a3d0fc891cd0b281b24e89592400d6e630141
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Shekhar Hansda
- S. P. Thipperudraswamy
- Siva Ananth Mariappan
- R. Shinde
- Pandiaraj Manickam
- A. Kaushik
- S. Murugesan
Citations in the corpus
- Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare (2022, background): “Neural Network (NN) • Cancer diagnosis [13,30–32] • Identifying Parkinson’s disease [33] • Image-based cardiac monitoring [22] • Alzheimer’s disease [34,35] • Surgery [25–27] • Sensor applications [36,37] • Diabetes prediction [38] • Human–machine interface [39] • Pandemic resource management [40] •”
- Nanomedicine-Driven Modulation of the Gut–Brain Axis: Innovative Approaches to Managing Chronic Inflammation in Alzheimer’s and Parkinson’s Disease (2025, unknown): “In the detection of AD, inception modules have also been used by InceptionV3 and InceptionV4 to optimize their computational efficiency [121–123].”