Machine Learning in the Classification of Pediatric Posterior Fossa Tumors: A Systematic Review.

ABSTRACT: Background: Posterior fossa tumors (PFTs) are a morbid group of central nervous system tumors that most often present in childhood. While early diagnosis is critical to drive appropriate treatment, definitive diagnosis is currently only achievable through invasive tissue collection and histopathological analyses. Machine learning has been investigated as an alternative means of diagnosis. In this systematic review and meta-analysis, we evaluated the primary literature to identify all machine learning algorithms developed to classify and diagnose pediatric PFTs using imaging or molecular data. Methods: Of the 433 primary papers identified in PubMed, EMBASE, and Web of Science, 25 ultimately met the inclusion criteria. The included papers were extracted for algorithm architectu

SUBMITTER: Yearley AG 

PROVIDER: S-EPMC9688156 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature