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Ensembling complex network ‘perspectives’ for mild cognitive impairment detection with artificial neural networks
- Source :
- Pattern Recognition Letters. 136:168-174
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- In this paper, we propose a novel method for mild cognitive impairment detection based on jointly exploiting the complex network and the neural network paradigm. In particular, the method is based on ensembling different brain structural “perspectives” with artificial neural networks. On one hand, these perspectives are obtained with complex network measures tailored to describe the altered brain connectivity. In turn, the brain reconstruction is obtained by combining diffusion-weighted imaging (DWI) data to tractography algorithms. On the other hand, artificial neural networks provide a means to learn a mapping from topological properties of the brain to the presence or absence of cognitive decline. The effectiveness of the method is studied on a well-known benchmark data set in order to evaluate if it can provide an automatic tool to support the early disease diagnosis. Also, the effects of balancing issues are investigated to further assess the reliability of the complex network approach to DWI data.
- Subjects :
- FOS: Computer and information sciences
Decision support system
Computer science
Computer Vision and Pattern Recognition (cs.CV)
Reliability (computer networking)
Computer Science - Computer Vision and Pattern Recognition
02 engineering and technology
Machine learning
computer.software_genre
01 natural sciences
Artificial Intelligence
0103 physical sciences
FOS: Electrical engineering, electronic engineering, information engineering
0202 electrical engineering, electronic engineering, information engineering
Cognitive decline
010306 general physics
Set (psychology)
Artificial neural network
business.industry
Image and Video Processing (eess.IV)
Electrical Engineering and Systems Science - Image and Video Processing
Complex network
FOS: Biological sciences
Quantitative Biology - Neurons and Cognition
Signal Processing
Neurons and Cognition (q-bio.NC)
020201 artificial intelligence & image processing
Computer Vision and Pattern Recognition
Artificial intelligence
business
computer
Software
Diffusion MRI
Tractography
Subjects
Details
- ISSN :
- 01678655
- Volume :
- 136
- Database :
- OpenAIRE
- Journal :
- Pattern Recognition Letters
- Accession number :
- edsair.doi.dedup.....7ab7df347173f1d0f0fa245091e3b60d