基于MRI影像组学机器学习模型在脊髓型颈椎病危险度分级中的价值OA北大核心CSTPCD
Study on the ability to grade the risk of cervical spondylotic myelopathy by using machine learning model based on MRI radiomics
目的 探讨基于MRI放射组学特征的机器学习(machine learning,ML)模型对脊髓型颈椎病(cervical spondylotic myelopathy,CSM)进行危险度分级的价值.材料与方法 回顾性分析临床诊断为CSM的患者病例317例,并使用日本骨科协会(Japanese Orthopaedic Association,JOA)评估治疗分数分为轻症组193例和中重度组124例.手动勾画脊髓轴位T2WI像生成感兴趣区(regio…查看全部>>
Objective:To explore the value of machine learning(ML)model based on MRI radiomics features in grading the risk of cervical spondylotic myelopathy(CSM).Materials and Methods:This retrospective study included 317 patients diagnosed with cervical spondylotic myelopathy(CSM),according to the Japanese Orthopaedic Association(JOA)score they were divided into mild CSM group(193 patients)and moderate-severe CSM group(124 patients).Spinal cord in the transverse T2-w…查看全部>>
徐刚;陈鹏;李宇龙;朱芸;谢宗玉
安徽理工大学附属淮南新华医院医学影像科,淮南 232000湖州市中心医院放射科,湖州 313000安徽理工大学附属淮南新华医院脊柱骨科,淮南 232000蚌埠医科大学第一附属医院放射科,蚌埠 233000蚌埠医科大学第一附属医院放射科,蚌埠 233000
临床医学
脊髓型颈椎病放射组学机器学习危险度分级磁共振成像
cervical spondylotic myelopathyradiomicsmachine learningrisk classificationmagnetic resonance imaging
《磁共振成像》 2024 (4)
50-55,77,7
Natural Science Research Project of Colleges and Universities in Anhui Province(No.2022AH051473)Key Research and Development Program of Anhui Province(No.2022e07020033). 安徽省高等学校自然科学研究项目(编号:2022AH051473)安徽省重点研究与开发计划项目(编号:2022e07020033)
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