AI-Based Denoising of Head Impact Kinematics Measurements With Convolutional Neural Network for Traumatic Brain Injury Prediction-Reference-Cited by-同舟云学术

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AI-Based Denoising of Head Impact Kinematics Measurements With Convolutional Neural Network for Traumatic Brain Injury Prediction

Published:2024-09 Issue:9 Volume:71 Page:2759-2770
ISSN:0018-9294
Container-title:IEEE Transactions on Biomedical Engineering
language:
Short-container-title:IEEE Trans. Biomed. Eng.

Author:

Zhan Xianghao¹^ORCID,Liu Yuzhe²^ORCID,Cecchi Nicholas J.¹^ORCID,Callan Ashlyn A.¹^ORCID,Le Flao Enora¹^ORCID,Gevaert Olivier³^ORCID,Zeineh Michael M.⁴^ORCID,Grant Gerald A.⁵^ORCID,Camarillo David B.¹^ORCID

Affiliation:

1. Department of Bioengineering, Stanford University, USA

2. School of Biological Science and Medical Engineering, BeiHang University, Beijing, China

3. Department of Biomedical Data Science, Stanford University, USA

4. Department of Radiology, Stanford University, USA

5. Department of Neurosurgery, Duke University, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/10/10643372/10510039.pdf?arnumber=10510039

Reference50 articles.

1. Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

2. A wearable hydraulic shock absorber with efficient energy dissipation

3. Translational models of mild traumatic brain injury tissue biomechanics

4. Neurodegenerative Disease Mortality among Former Professional Soccer Players

5. Chronic neuropathologies of single and repetitive TBI: substrates of dementia?

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