48 citations · 53 across the 5 of their papers we have counts for
5 papers
Modeling Alzheimer's Disease: Bayesian Copula Graphical Model from Demographic, Cognitive, and Neuroimaging Data
Lucas Vogels, Reza Mohammadi, Marit Schoonhoven +2
The early detection of Alzheimer's disease (AD) requires an understanding of the relationships between a wide range of features. Conditional independencies and partial correlations…
Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease
Martin Dyrba, Moritz Hanzig, Slawek Altenstein +37
Background: Although convolutional neural networks (CNN) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI)…
Learning Shape Features and Abstractions in 3D Convolutional Neural Networks for Detecting Alzheimer's Disease
Md Motiur Rahman Sagar, Martin Dyrba
Deep Neural Networks - especially Convolutional Neural Network (ConvNet) has become the state-of-the-art for image classification, pattern recognition and various computer vision t…
Comparison of Convolutional neural network training parameters for detecting Alzheimers disease and effect on visualization
Arjun Haridas Pallath, Martin Dyrba
Convolutional neural networks (CNN) have become a powerful tool for detecting patterns in image data. Recent papers report promising results in the domain of disease detection usin…
Gaussian graphical models reveal inter-modal and inter-regional conditional dependencies of brain alterations in Alzheimer's disease
Martin Dyrba, Reza Mohammadi, Michel J. Grothe +2
Alzheimer's disease (AD) is characterized by a sequence of pathological changes, which are commonly assessed in vivo using MRI and PET. Currently, the most approaches to analyze st…