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Recent advances in the use of deep learning and artificial intelligence in the diagnosis and treatment of cervical and lumbar spine degenerative diseases
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Qiang-Hui Shi, Zi-Fan Zhang, Bo Hu, Peng Cao, Chen Xu*, Wen Yuan, Hua-Jiang Chen
Medical Journal of Chinese People’s Liberation Army | 2021, 46(10) : 1034 - 1039
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Medical Journal of Chinese People’s Liberation Army | 2021, 46(10): 1034-1039
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Recent advances in the use of deep learning and artificial intelligence in the diagnosis and treatment of cervical and lumbar spine degenerative diseases
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Qiang-Hui Shi, Zi-Fan Zhang, Bo Hu, Peng Cao, Chen Xu*, Wen Yuan, Hua-Jiang Chen
Affiliations
  • Department of Orthopedics, the Second Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Published: 2021-10-28 doi: 10.11855/j.issn.0577-7402.2021.10.13
Outline
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Deep learning (DL), as a branch of artificial intelligence, is the mainstream artificial intelligence recognition method for image, voice and language. In recent years, it has attracted more and more attention in the medical field. The DL technique characterizes and analyzes the original features of a particular large amount of data. By using a multi-layered machine learning model, it simulates the activity of neurons in the brain and finally the computer outputs a single diagnosis. With reference to related research findings in China and foreign countries, this paper introduces the advances of its development and application in the diagnosis and treatment of spinal degenerative diseases such as lumbar disc herniation and cervical spondylosis, as well as its future prospetive.

artificial intelligence  /  deep learning  /  cervical spondylosis  /  lumbar disc herniation
Qiang-Hui Shi, Zi-Fan Zhang, Bo Hu, Peng Cao, Chen Xu, Wen Yuan, Hua-Jiang Chen. Recent advances in the use of deep learning and artificial intelligence in the diagnosis and treatment of cervical and lumbar spine degenerative diseases[J]. Medical Journal of Chinese People’s Liberation Army, 2021 , 46 (10) : 1034 -1039 . DOI: 10.11855/j.issn.0577-7402.2021.10.13
Funding
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  • National Natural Science Foundation of China(82072471)
  • National Natural Science Foundation of China(82072469)
  • Shanghai Rising-Star Program(20QA1409200)
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Year 2021 volume 46 Issue 10
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Article Info
doi: 10.11855/j.issn.0577-7402.2021.10.13
  • Receive Date：2021-01-29
  • Online Date：2025-12-19
  • Published：2021-10-28
Article Data
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History
  • Received：2021-01-29
  • Revised：2021-04-29
Funding
National Natural Science Foundation of China(82072471)
National Natural Science Foundation of China(82072469)
Shanghai Rising-Star Program(20QA1409200)
Affiliations
    Department of Orthopedics, the Second Affiliated Hospital of Naval Medical University, Shanghai 200433, China

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Citations
表12种不同金属材料的力学参数
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Family		 属数
Number of
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Number of
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Percentage of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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