Incorporating multiple magnetic resonance diffusion models to differentiate low- and high-grade adult gliomas: a machine learning approach

BACKGROUND: Accurate grading of gliomas is a challenge in imaging diagnosis. This study aimed to evaluate the performance of a machine learning (ML) approach based on multiparametric diffusion-weighted imaging (DWI) in differentiating low- and high-grade adult gliomas. METHODS: A model was developed...

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Detalles Bibliográficos
Autores principales: Xu, Junqi, Ren, Yan, Zhao, Xueying, Wang, Xiaoqing, Yu, Xuchen, Yao, Zhenwei, Zhou, Yan, Feng, Xiaoyuan, Zhou, Xiaohong Joe, Wang, He
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9622457/
https://www.ncbi.nlm.nih.gov/pubmed/36330178
http://dx.doi.org/10.21037/qims-22-145

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9622457/
https://www.ncbi.nlm.nih.gov/pubmed/36330178
http://dx.doi.org/10.21037/qims-22-145

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