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Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment.

Gabriel Cassinelli PetersenJ ShatalovT VermaW R BrimHarry SubramanianAlexandria BrackettRyan C BaharSara MerkajTal ZeeviLawrence H StaibJin CuiAntonio OmuroRichard A BronenJoseph SchindlerMariam S Aboian
Published in: AJNR. American journal of neuroradiology (2022)
Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.
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