Development and validation of a multimodal feature fusion prognostic model for lumbar degenerative disease based on machine learning: a study protocol.

ABSTRACT:

Introduction

Lumbar degenerative disease (LDD) is one of the most common reasons for patients to present with low back pain. Proper evaluation and treatment of patients with LDD are important, which clinicians perform using a variety of predictors for guidance in choosing the most appropriate treatment. Because evidence on which treatment is best for LDD is limited, the purpose of this study is to establish a clinical prediction model based on machine learning (ML) to accurately predict outcomes of patients with LDDs in the early stages by their clinical characteristics and imaging changes.

Methods and analysis

In this study, we develop and validate a clinical prognostic model to determine whether patients will experience complications within 6 months after percutaneous endo

SUBMITTER: Wang Z 

PROVIDER: S-EPMC10481837 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature