Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation
Abstract The purpose of this study was to establish a high-performing radiomics strategy with machine learning from conventional and diffusion MRI to differentiate recurrent glioblastoma (GBM) from radiation necrosis (RN) after concurrent chemoradiotherapy (CCRT) or radiotherapy. Eighty-six patients...
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Autores principales: | Yae Won Park, Dongmin Choi, Ji Eun Park, Sung Soo Ahn, Hwiyoung Kim, Jong Hee Chang, Se Hoon Kim, Ho Sung Kim, Seung-Koo Lee |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/598a029341804dad921fdd8916fdd626 |
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