Machine learning-based cluster analysis identifies four unique phenotypes of patients with degenerative cervical myelopathy with distinct clinical profiles and long-term functional and neurological outcomes-Reference-Cited by-同舟云学术

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Machine learning-based cluster analysis identifies four unique phenotypes of patients with degenerative cervical myelopathy with distinct clinical profiles and long-term functional and neurological outcomes

Published:2024-08 Issue: Volume:106 Page:105226
ISSN:2352-3964
Container-title:eBioMedicine
language:en
Short-container-title:eBioMedicine

Author:

Pedro Karlo M.^ORCID,Alvi Mohammed Ali^ORCID,Hejrati Nader^ORCID,Quddusi Ayesha I.,Singh Anoushka,Fehlings Michael G.^ORCID

Publisher

Elsevier BV

Reference37 articles.

1. The frequency of various “myelopathic symptoms” in cervical myelopathy: evaluation in a large surgical cohort;Niu;Clin Spine Surg,2020

2. Comparing quality of life in cervical spondylotic myelopathy with other chronic debilitating diseases using the short form survey 36-health survey;Oh;World Neurosurg,2017

3. Establishing diagnostic criteria for degenerative cervical myelopathy [AO spine RECODE-DCM research priority number 3];Hilton;Global Spine J,2022

4. Prevalence of neck pain in patients with degenerative cervical myelopathy and short-term response after operative treatment: a cohort study of 664 patients from 26 global sites;Schneider;Global Spine J,2022

5. Cervical spondylotic myelopathy with severe axial neck pain: is anterior or posterior approach better?;Chan;J Neurosurg Spine,2022

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