Robust performance of deep learning for distinguishing glioblastoma from single brain metastasis using radiomic features: model development and validation

We evaluated the diagnostic performance and generalizability of traditional machine learning and deep learning models for distinguishing glioblastoma from single brain metastasis using radiomics. The training and external validation cohorts comprised 166 (109 glioblastomas and 57 metastases) and 82...

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Detalles Bibliográficos
Autores principales: Bae, Sohi, An, Chansik, Ahn, Sung Soo, Kim, Hwiyoung, Han, Kyunghwa, Kim, Sang Wook, Park, Ji Eun, Kim, Ho Sung, Lee, Seung-Koo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374174/
https://www.ncbi.nlm.nih.gov/pubmed/32694637
http://dx.doi.org/10.1038/s41598-020-68980-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374174/
https://www.ncbi.nlm.nih.gov/pubmed/32694637
http://dx.doi.org/10.1038/s41598-020-68980-6

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