Non-linear dynamic state-space network modeling for decoding neurodegeneration-Reference-Cited by-同舟云学术

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Non-linear dynamic state-space network modeling for decoding neurodegeneration

Published:2023-12-21 Issue:9 Volume:19 Page:1879-1880
ISSN:1673-5374
Container-title:Neural Regeneration Research
language:en
Short-container-title:

Author:

Chirumamilla Venkata C.¹,Ip Chi Wang²,Reich Martin²,Peach Robert²,Volkmann Jens²,Nasseroleslami Bahman³,Muthuraman Muthuraman²^ORCID

Affiliation:

1. Prenatal Pediatrics Institute, Children's National Hospital, Washington, DC, USA

2. Neural Engineering with Signal Analytics and Artificial Intelligence, Department of Neurology, University of Würzburg, Würzburg, Germany

3. Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland

Publisher

Medknow

Subject

Developmental Neuroscience

Reference12 articles.

1. Early diagnosis of neurodegenerative diseases using CNN-LSTM and wavelet transform;Amooei;J Healthc Inform Res,2023

2. The role of genetics for biomarker development in neurodegeneration;Bertram;Prog Neurobiol,2011

3. The role of ipsilateral motor network in upper limb movement;Ding;Front Physiol,2023

4. Parkinson's detection based on combined CNN and LSTM using enhanced speech signals with Variational mode decomposition;Er;Biomed Signal Process Control,2021

5. Frontal lobe connectivity and network community characteristics are associated with the outcome of subthalamic nucleus deep brain stimulation in patients with Parkinson's disease;Koirala;Brain Topogr,2017

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