Development and Internal Validation of Supervised Machine Learning Algorithm for Predicting the Risk of Recollapse Following Minimally Invasive Kyphoplasty in Osteoporotic Vertebral Compression Fractures

Development and Internal Validation of Supervised Machine Learning Algorithm for Predicting the Risk of Recollapse Following Minimally Invasive Kyphoplasty in Osteoporotic Vertebral Compression Fractures

BackgroundThe published literatures indicate that patients with osteoporotic vertebral compression fractures (OVCFs) benefit significantly from percutaneous kyphoplasty (PKP), but this surgical technique is associated with frequent postoperative recollapse, a complication that severely limits long-t...

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Bibliographic Details
Main Authors: Sheng-tao Dong, Jieyang Zhu, Hua Yang, Guangyi Huang, Chenning Zhao, Bo Yuan
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Public Health
Subjects:
support vector machine
recollapse
osteoporotic vertebral compression fractures
percutaneous kyphoplasty
risk factors
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2022.874672/full

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https://www.frontiersin.org/articles/10.3389/fpubh.2022.874672/full

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