The differential diagnosis value of radiomics-based machine learning in Parkinson's disease: a systematic review and meta-analysis.

ABSTRACT:

Background

In recent years, radiomics has been increasingly utilized for the differential diagnosis of Parkinson's disease (PD). However, the application of radiomics in PD diagnosis still lacks sufficient evidence-based support. To address this gap, we carried out a systematic review and meta-analysis to evaluate the diagnostic value of radiomics-based machine learning (ML) for PD.

Methods

We systematically searched Embase, Cochrane, PubMed, and Web of Science databases as of November 14, 2022. The radiomics quality assessment scale (RQS) was used to evaluate the quality of the included studies. The outcome measures were the c-index, which reflects the overall accuracy of the model, as well as sensitivity and specificity. During this meta-analysis, we discussed the differen

SUBMITTER: Bian J 

PROVIDER: S-EPMC10357514 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature