Use of multivariate linear regression and support vector regression to predict functional outcome after surgery for cervical spondylotic myelopathy

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Use of multivariate linear regression and support vector regression to predict functional outcome after surgery for cervical spondylotic myelopathy.

This study introduces the use of multivariate linear regression (MLR) and support vector regression (SVR) models to predict postoperative outcomes in a cohort of patients who underwent surgery for cervical spondylotic myelopathy (CSM). Currently, predicting outcomes after surgery for CSM remains a challenge. We recruited patients who had a diagnosis of CSM and required decompressive surgery wit...

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Cervical Spondylotic Myelopathy: Functional Outcome after Modified Hirabayashi Laminoplasty

Spondylotic myelopathy is an old age problem of cervical spine. Different modes of treatment are available. Surgical intervention is indicated when conservative trials failed. Traditional laminectomy may cause multiple complications especially kyphotic deformity and epidural scarring. To avoid these complications a variety of laminoplasties were evolved in Japan as an alternative to laminectomy...

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Clinical Outcome after Laminectomy without Fusion for Cervical Spondylotic Myelopathy

Dorsal decompression in patients, presenting with cervical spondylotic myelopathy with no signs of instability, is a standard surgical option. Laminectomy or laminoplasty is applied to reduce the pressure on the myelon. The aim of this study was to evaluate the clinical outcome in a consecutive series of patients. This retrospective study included a total of 65 patients who underwent laminectom...

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ژورنال

عنوان ژورنال: Journal of Clinical Neuroscience

سال: 2015

ISSN: 0967-5868

DOI: 10.1016/j.jocn.2015.04.002