Methodological quality of radiomic-based prognostic studies in gastric cancer: a cross-sectional study.

ABSTRACT:

Background

Machine learning radiomics models are increasingly being used to predict gastric cancer prognoses. However, the methodological quality of these models has not been evaluated. Therefore, this study aimed to evaluate the methodological quality of radiomics studies in predicting the prognosis of gastric cancer, summarize their methodological characteristics and performance.

Methods

The PubMed and Embase databases were searched for radiomics studies used to predict the prognosis of gastric cancer published in last 5 years. The characteristics of the studies and the performance of the models were extracted from the eligible full texts. The methodological quality, reporting completeness and risk of bias of the included studies were evaluated using the RQS, TRIPOD and PR

SUBMITTER: Jiang T 

PROVIDER: S-EPMC10507631 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature