Brain metastasis detection using machine learning: a systematic review and meta-analysis.

ABSTRACT:

Background

Accurate detection of brain metastasis (BM) is important for cancer patients. We aimed to systematically review the performance and quality of machine-learning-based BM detection on MRI in the relevant literature.

Methods

A systematic literature search was performed for relevant studies reported before April 27, 2020. We assessed the quality of the studies using modified tailored questionnaires of the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) criteria and the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Pooled detectability was calculated using an inverse-variance weighting model.

Results

A total of 12 studies were included, which showed a clear transition from classical machine learning (cML) to deep learning (DL)

SUBMITTER: Cho SJ 

PROVIDER: S-EPMC7906058 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature