Machine Learning Applications for Differentiation of Glioma from Brain Metastasis-A Systematic Review.

ABSTRACT: Glioma and brain metastasis can be difficult to distinguish on conventional magnetic resonance imaging (MRI) due to the similarity of imaging features in specific clinical circumstances. Multiple studies have investigated the use of machine learning (ML) models for non-invasive differentiation of glioma from brain metastasis. Many of the studies report promising classification results, however, to date, none have been implemented into clinical practice. After a screening of 12,470 studies, we included 29 eligible studies in our systematic review. From each study, we aggregated data on model design, development, and best classifiers, as well as quality of reporting according to the TRIPOD statement. In a subset of eligible studies, we conducted a meta-analysis of the reported AUC. It was fo

SUBMITTER: Jekel L 

PROVIDER: S-EPMC8946855 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature