A Deep Learning–Based Framework for Supporting Clinical Diagnosis of Glioblastoma Subtypes

Understanding molecular features that facilitate aggressive phenotypes in glioblastoma multiforme (GBM) remains a major clinical challenge. Accurate diagnosis of GBM subtypes, namely classical, proneural, and mesenchymal, and identification of specific molecular features are crucial for clinicians f...

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Detalles Bibliográficos
Autores principales: Munquad, Sana, Si, Tapas, Mallik, Saurav, Das, Asim Bikas, Zhao, Zhongming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9000988/
https://www.ncbi.nlm.nih.gov/pubmed/35419027
http://dx.doi.org/10.3389/fgene.2022.855420

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9000988/
https://www.ncbi.nlm.nih.gov/pubmed/35419027
http://dx.doi.org/10.3389/fgene.2022.855420

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