Development and Validation of a Machine Learning-Based Online Prognostic Model for Cervical Spondylosis Patients After Anterior Cervical Discectomy and Fusion: A Multicenter Study.

ABSTRACT:

Background

Cervical spondylosis (CS) is a degenerative condition often requiring surgical intervention, such as anterior cervical discectomy and fusion (ACDF), to alleviate symptoms. However, postoperative outcomes can vary significantly. This study aimed to develop and validate a predictive model for 1-year outcomes in CS patients after ACDF using multiple machine learning algorithms.

Methods

Data from 973 patients across three clinical centers, including 872 patients in the retrospective cohort and 101 patients in the prospective cohort, were utilized. A variety of clinical and laboratory features were identified using LASSO regression. Various machine learning algorithms were employed to develop predictive models. The models' performance was assessed and compared using me

SUBMITTER: Feng S 

PROVIDER: S-EPMC12302979 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature