Authors
Y Hai, J X Huang, Z H Feng
Published in
Zhonghua yi xue za zhi. Volume 106. Issue 34. Pages 3535-3539. Sep 15, 2026.
Abstract
Spinal deformity, characterized by complex anatomical structures and significant individual heterogeneity, is a highly challenging disease in the field of orthopedics. The traditional "experience-driven" clinical decision-making model has limitations, such as strong subjectivity and insufficient standardization. The application of artificial intelligence (AI) technology, especially deep learning in medical image analysis, risk prediction, and surgical planning, has brought revolutionary opportunities to spinal deformity surgery. From the perspectives of clinical experts, this article systematically expounds on the application progress and value of AI in core links, such as imaging parameter measurement, surgical risk prediction, and individualized plan formulation, analyzes the bottlenecks in technology promotion, and looks forward to the development direction of "human-machine co-intelligence". The article emphasizes that through the integration with clinical experience, AI promotes the transformation of the discipline from "standardized treatment" to "individualized precision treatment", and constructs an intelligent diagnosis and treatment system.
PMID:
42736115
Bibliographic data and abstract were imported from PubMed on 15 Sep 2026.
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