Elizabeth M. Davenport
Orcid: 0000-0002-8765-6584Affiliations:
- University of Texas Southwestern, Dallas, TX, USA
According to our database1,
Elizabeth M. Davenport
authored at least 13 papers
between 2012 and 2024.
Collaborative distances:
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Bibliography
2024
J. Imaging, April, 2024
2021
MEGnet: Automatic ICA-based artifact removal for MEG using spatiotemporal convolutional neural networks.
NeuroImage, 2021
2020
Brain Connect., 2020
2018
Quantifying the association between white matter integrity changes and subconcussive head impact exposure from a single season of youth and high school football using 3D convolutional neural networks.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football players.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
Automatic 1D convolutional neural network-based detection of artifacts in MEG acquired without electrooculography or electrocardiography.
Proceedings of the 2017 International Workshop on Pattern Recognition in Neuroimaging, 2017
Using Convolutional Neural Networks to Automatically Detect Eye-Blink Artifacts in Magnetoencephalography Without Resorting to Electrooculography.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Changes in resting state MRI networks from a single season of football distinguishes controls, low, and high head impact exposure.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
Automatic identification of successful memory encoding in stereo-eeg of refractory, mesial temporal lobe epilepsy.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
2014
Graph theoretical analysis of resting-state MEG data: Identifying interhemispheric connectivity and the default mode.
NeuroImage, 2014
Relational learning helps in three-way classification of Alzheimer patients from structural magnetic resonance images of the brain.
Int. J. Mach. Learn. Cybern., 2014
2012
A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012