深度学习在腰椎疾病诊断、手术规划及术后预测中的应用研究进展

doi:10.3969/j.issn.1006-5725.2025.06.023

Abstract

Abstract:

Deep learning （DL） is a machine learning technique that emulates the human brain's functionality through multi?layered neural network models， enabling it to learn and extract features from data， thereby facilitating the automatic processing and learning of complex tasks. DL has achieved numerous significant breakthroughs in areas such as image recognition， speech recognition， and natural language processing， becoming one of the most prominent technologies in the field of artificial intelligence. With the rapid advancement of DL technology， its application in the medical field has yielded remarkable outcomes， offering new possibilities for the diagnosis and treatment of lumbar diseases. This review aims to elucidate the application and research progress of DL in diagnosing， planning surgeries， and predicting postoperative efficacy for lumbar spine diseases.

Key words: deep learning, neural network, lumbar spine disease, computer-aided diagnosis, lumbar spine imaging analysis

CLC Number:

R459.9

Gaokai HU,Ya'nan NIU,Yukang GONG,Yang HU,Ruixuan XU,Wenshan. GAO. Research progress on the application of deep learning in lumbar spine disease[J]. The Journal of Practical Medicine, 2025, 41(6): 921-928.

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Research progress on the application of deep learning in lumbar spine disease

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