Pelvic Incidence-Dependent Clustering of Sagittal Spinal Alignment in Asymptomatic Middle-Aged and Elderly Adults: A Machine Learning Approach.

Abstract

Authors

• Qijun Wang
  Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.
• Dongfan Wang
  Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.
• Xiangyu Li
• Weiguo Zhu
  Department of General Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
• Peng Cui
  School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Minhang, Shanghai 200240. China.
• Zheng Wang
  Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan 430060, China.
• Wei Wang
  State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
• Jeffrey C Wang
  Department of Orthopaedic Surgery, University of Southern California, Orthopaedic SurgeryHC4 -1450 San Pablo St, #5400 Health Sciences Campus, Los Angeles, CA 90033, USA.
• Xiaolong Chen
  Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.
• Shibao Lu
  Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.

Keywords

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