Classification of Patients with Cervical Spondylotic Myelopathy using Machine Learning and Brain Network Analysis-Reference-Cited by-同舟云学术

Classification of Patients with Cervical Spondylotic Myelopathy using Machine Learning and Brain Network Analysis

Published:2023-10-27 Issue: Volume:201 Page:304-310
ISSN:
Container-title:2023 12th International Conference on Computing and Pattern Recognition
language:
Short-container-title:

Author:

Li Shen¹^ORCID,Yang Banghua²^ORCID,Dou Yibo³^ORCID,Wang Yongli³^ORCID,Ma Jun⁴^ORCID,Cao Peng³^ORCID

Affiliation:

1. School of Medicine, Shanghai University, China

2. School of Mechanical and Electrical Engineering and Automation, Shanghai University, China and School of Medicine, Shanghai University, China

3. Department of Cervical Surgery, The Second Affiliated Hospital of the Naval Medical University, China

4. School of Mechanical and Electrical Engineering and Automation, Shanghai University, China

Funder

Shanghai Industrial Collaborative Technology Innovation Project

National Key Research and Development Program of China

Shanghai Major Science and technology Project

National Natural Science Foundation of China

National Defense Basic Scientific Research Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3633637.3633685

Reference15 articles.

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2. Zhao G Zhang C Zhan Y He L. The Correlation between Functional Connectivity of the Primary Somatosensory Cortex and Cervical Spinal Cord Microstructural Injury in Patients with Cervical Spondylotic Myelopathy. Disease Markers. 2022;2022.

3. Cao Y Zhan Y Du M Zhao G Liu Z Zhou F Disruption of human brain connectivity networks in patients with cervical spondylotic myelopathy. Quantitative Imaging in Medicine and Surgery. 2021;11:3418-+.

4. Kuang C Zha Y Liu C Chen J. Altered Topological Properties of Brain Structural Covariance Networks in Patients With Cervical Spondylotic Myelopathy. Frontiers in Human Neuroscience. 2020;14.

5. Kuang YX Wu ZY Xia R Li XJ Liu J Dai YL Phase Lag Index of Resting-State EEG for Identification of Mild Cognitive Impairment Patients with Type 2 Diabetes. Brain Sciences. 2022;12.