Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors

OBJECTIVE: To assess whether radiomics features derived from multiparametric MRI can predict the tumor grade of lower-grade gliomas (LGGs; World Health Organization grade II and grade III) and the nonenhancing LGG subgroup. MATERIALS AND METHODS: Two-hundred four patients with LGGs from our institut...

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Bibliografiset tiedot
Julkaisussa:Korean J Radiol
Päätekijät: Park, Yae Won, Choi, Yoon Seong, Ahn, Sung Soo, Chang, Jong Hee, Kim, Se Hoon, Lee, Seung-Koo
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: The Korean Society of Radiology 2019
Aiheet:
Neuroimaging and Head & Neck
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC6715562/
https://ncbi.nlm.nih.gov/pubmed/31464116
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3348/kjr.2018.0814
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