Which supervised machine learning algorithm can best predict achievement of minimum clinically important difference in neck pain after surgery in patients with cervical myelopathy? A QOD study

Park, C., Mummaneni, P. V., Gottfried, O. N., Shaffrey, C. I., Tang, A. J., Bisson, E. F., Asher, A. L., Coric, D., Potts, E. A., Foley, K. T., Wang, M. Y., Fu, K.-M., Virk, M. S., Knightly, J. J., Meyer, S., Park, P., Upadhyaya, C., Shaffrey, M. E., Buchholz, A. L., … Chan, A. K. (2023). Which supervised machine learning algorithm can best predict achievement of minimum clinically important difference in neck pain after surgery in patients with cervical myelopathy? A QOD study. Neurosurgical Focus, 54(6), E5. https://doi.org/10.3171/2023.3.focus2372
Authors:
Christine Park
Praveen V Mummaneni
Oren N Gottfried
Christopher I Shaffrey
Anthony J Tang
Erica F Bisson
Anthony L Asher
Domagoj Coric
Eric A Potts
Kevin T Foley
Michael Y Wang
Kai-Ming Fu
Michael S Virk
John J Knightly
Scott Meyer
Paul Park
Cheerag Upadhyaya
Mark E Shaffrey
Avery L Buchholz
Luis M Tumialán
Jay D Turner
Brandon A Sherrod
Nitin Agarwal
Dean Chou
Regis W Haid
Mohamad Bydon
Andrew K Chan
Affiliated Authors:
Anthony J Tang
Dean Chou
Andrew K Chan
Subjects:
Author Keywords:
quality outcomes database
cervical spondylotic myelopathy
machine learning
neck pain
patient satisfaction
patient-reported outcomes
Publication Type:
Article
Unique ID:
10.3171/2023.3.focus2372
PMID:
Publication Date:
Data Source:
PubMed

Record Created: