可预测腰椎间融合器沉降风险的人工智能预测模型  

Artificial intelligence prediction model for the risk of lumbar interbody cage subsidence

作　　者：王犇 欧云生[1] Wang Ben;Ou Yunsheng(Dept of Orthopedics,The First Affiliated Hospital of Chongqing Medical University,Chongqing 400016)

机构地区：[1]重庆医科大学附属第一医院骨科脊柱外科病区,重庆400016

出　　处：《安徽医科大学学报》2020年第7期1144-1146,共3页Acta Universitatis Medicinalis Anhui

基　　金：国家自然科学基金面上项目(编号:81572634)。

摘　　要：研究鉴定沉降相关风险因素(融合阶段数目、术前/术后椎间隙高度、术后节段前凸角以及术后PT、SS),并以此为基础构建高斯核SVM模型,其预测术后融合器沉降风险的AUC为0.93。此结果将有助于精准医学在脊柱外科的发展。A Graussian kernel SVM model was constructed based on identified risk factors(including number of surgical segments,preoperative/postoperative intervertebral height,postoperative L4 segment lordosis,and postoperative PT,SS)related to cage subsidence.The AUC was 0.93.The results will help the development of precision medicine in spine surgery.

关 键 词：人工智能 椎间融合器沉降 脊柱外科 

分 类 号：R687.1[医药卫生—骨科学]