Machine Learning Approach to Differentiation of Peripheral Schwannomas and Neurofibromas: A Multi-Center Study.
Michael ZhangElizabeth TongSam WongForrest HamrickMaryam MohammadzadehVaishnavi RaoCourtney PendletonBrandon W SmithNicholas F HugSandip BiswalJayne SeekinsSandy NapelRobert J SpinnerMark A MahanKristen W YeomThomas J WilsonPublished in: Neuro-oncology (2021)
The radiomics-based classifiers developed here proved to be more accurate and had a higher AUC on the ROC curve than expert human evaluators. This demonstrates that radiomics using routine MRI sequences and clinical features can aid in differentiation of peripheral schwannomas and neurofibromas.