Application of graph convolutional neural networks to Alzheimer's and Parkinson's disease classification
Identifying connectivity patterns of the human structural connectome plays an important role in diagnosing various neurodegenerative conditions including Alzheimer’s disease (AD) and Parkinson’s disease (PD). The structural connectome is measured by diffusion weighted imaging (DTI) scans and is repr...
Saved in:
Main Author: | Goli, Haveesh |
---|---|
Other Authors: | Jagath C Rajapakse |
Format: | Thesis-Master by Research |
Language: | English |
Published: |
Nanyang Technological University
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/148634 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Pre-training 3D convolutional neural networks for prodromal alzheimer's disease classification
by: Jiang, Hongchao, et al.
Published: (2022) -
Classification of pomelo leaf diseases using convolution neural network
by: Sirirat Laosim, et al.
Published: (2022) -
Graph convolutional neural networks for text categorization
by: Lakhotia, Suyash
Published: (2018) -
Investigating subtypes of alzheimer's disease using graph neural networks on functional MRI scans
by: Ang, Jun Liang
Published: (2021) -
Fast convolutional neural network for image classification
by: Jeon, Young Seok
Published: (2017)