Prediction of Pseudoprogression versus Progression using Machine Learning Algorithm in Glioblastoma

We aimed to investigate the feasibility of machine learning (ML) algorithm to distinguish pseudoprogression (PsPD) from progression (PD) in patients with glioblastoma (GBM). We recruited the patients diagnosed as primary GBM who received gross total resection (GTR) and concurrent chemoradiotherapy i...

Descripción completa

Detalles Bibliográficos
Autores principales: Jang, Bum-Sup, Jeon, Seung Hyuck, Kim, Il Han, Kim, In Ah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104063/
https://www.ncbi.nlm.nih.gov/pubmed/30131513
http://dx.doi.org/10.1038/s41598-018-31007-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104063/
https://www.ncbi.nlm.nih.gov/pubmed/30131513
http://dx.doi.org/10.1038/s41598-018-31007-2

Ejemplares similares