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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...
Autores principales: | Park, Yae Won, Choi, Yoon Seong, Ahn, Sung Soo, Chang, Jong Hee, Kim, Se Hoon, Lee, Seung-Koo |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Radiology
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715562/ https://www.ncbi.nlm.nih.gov/pubmed/31464116 http://dx.doi.org/10.3348/kjr.2018.0814 |
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