Machine Learning Models for Classifying High- and Low-Grade Gliomas: A Systematic Review and Quality of Reporting Analysis

Machine Learning Models for Classifying High- and Low-Grade Gliomas: A Systematic Review and Quality of Reporting Analysis

ObjectivesTo systematically review, assess the reporting quality of, and discuss improvement opportunities for studies describing machine learning (ML) models for glioma grade prediction.MethodsThis study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic T...

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Bibliographic Details
Main Authors: Ryan C. Bahar, Sara Merkaj, Gabriel I. Cassinelli Petersen, Niklas Tillmanns, Harry Subramanian, Waverly Rose Brim, Tal Zeevi, Lawrence Staib, Eve Kazarian, MingDe Lin, Khaled Bousabarah, Anita J. Huttner, Andrej Pala, Seyedmehdi Payabvash, Jana Ivanidze, Jin Cui, Ajay Malhotra, Mariam S. Aboian
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-04-01
Series:Frontiers in Oncology
Subjects:
machine learning
deep learning
artificial intelligence
glioma
systematic review
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.856231/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2022.856231/full

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