Advances in machine learning models for cervical spondylosis(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2025年第2期
- Page:
- 269-273
- Research Field:
- 医学人工智能
- Publishing date:
Info
- Title:
- Advances in machine learning models for cervical spondylosis
- Author(s):
- YANG Wentong; ZHAO Jirong; XUE Xu; MA Dong; ZHAO Rui; LIU Junhao; MA Boqian
- Clinical College of Traditional Chinese Medicine, Gansu University of Chinese Medicine, Lanzhou 730030, China
- Keywords:
- Keywords: cervical spondylosis machine learning deep learning review
- PACS:
- R318；653
- DOI:
- DOI:10.3969/j.issn.1005-202X.2025.02.020
- Abstract:
- Abstract： The diagnosis, treatment, and prognosis evaluation of cervical spondylosis are challenging in clinic. Machine learning (ML) models can improve the accuracy and efficiency of cervical spondylosis diagnosis by processing complex clinical data, assist in selecting more precise treatment plans, and evaluate prognosis. Through the domestic and foreign literature review on the application of ML models in cervical spondylosis in recent years, the study classifies and summarizes the relevant models applied in the diagnosis, treatment, and prognosis evaluation of cervical spondylosis, introduces classic algorithms such as random forest, as well as new algorithms such as convolutional neural networks, deep neural networks and long short-term memory networks, aiming to provide reference ML solutions for various stages of cervical spondylosis diagnosis and treatment.
Last Update: 2025-01-22