Predictive value of radiomics-based machine learning for the disease-free survival in breast cancer: a systematic review and meta-analysis

ABSTRACT:

Purpose

This study summarized the previously-published studies regarding the use of radiomics-based predictive models for the identification of breast cancer-associated prognostic factors, which can help clinical decision-making and follow-up strategy.

Materials and methods

This study has been pre-registered on PROSPERO. PubMed, Embase, Cochrane Library, and Web of Science were searched, from inception to April 23, 2022, for studies that used radiomics for prognostic prediction of breast cancer patients. Then the search was updated on July 18, 2023. Quality assessment was conducted using the Radiomics Quality Score, and meta-analysis was performed using R software.

Results

A total of 975 articles were retrieved, and 13 studies were included, involving 5014 partic

SUBMITTER: Lu D 

PROVIDER: S-EPMC10469000 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature