Progress of the application of deep learning in degenerative cervical myelopathy
10.11855/j.issn.0577-7402.1106.2025.0121
- VernacularTitle:深度学习技术在退行性脊髓型颈椎病中的应用研究进展
- Author:
Qian-Bo SONG
1
;
Qian DU
;
Yan ZENG
;
Yuan-Ming LU
;
Wen-Xing LIAO
;
Dong ZHAO
;
Guang-Ru CAO
Author Information
1. 遵义医科大学第二附属医院骨外科,贵州遵义 563000
- Keywords:
deep learning;
degenerative cervical myelopathy;
artificial intelligence;
neural networks
- From:
Medical Journal of Chinese People's Liberation Army
2025;50(10):1256-1262
- CountryChina
- Language:Chinese
-
Abstract:
Degenerative cervical myelopathy(DCM)is a group of diseases caused by cervical spine degeneration that compresses the spinal cord.It is a major cause of spinal cord dysfunction in adults,and its incidence is increasing globally.In the late stage,DCM could lead to paralysis due to spinal cord injury,which makes rapid,effective,and accurate medical diagnosis clinically significant.Deep learning(DL)technology can assist physicians in the rapid and accurate diagnosis of DCM by analyzing and processing a large amount of imaging data to extract features of the affected regions.In recent years,DL algorithm models have been leveraged for DCM-related research,which has become a focal point of intelligent medical development.In this review,domestic and international literature is surveyed,and the research progress and application of DL technology in the auxiliary diagnosis and prognosis evaluation of DCM are systematically summarized,aiming to provide a reference for intelligent diagnosis in clinical practice.
