Evaluating the efficacy of machine learning in predicting postherpetic neuralgia: a systematic review and meta-analysis.

ABSTRACT:

Introduction

The prediction of postherpetic neuralgia (PHN) is of great clinical significance. PHN prediction based on machine learning have received extensive attention in recent years. This study aims to conduct a comprehensive evaluation of machine learning in PHN prediction and provide guidance for the future models.

Method

The system retrieved the relevant literatures published in the PubMed, Web of Science, Embase and Cochrane Library databases from the establishment of the database to May 2025. Literature screening and data extraction were conducted in accordance with the PRISMA guidelines. According to the heterogeneity, the fixed-effect or the random-effect model was selected for data synthesis. The potential sources of heterogeneity were further explored through su

SUBMITTER: Lin Z 

PROVIDER: S-EPMC12476998 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature