Imaging habitats can predict early progression and characterise treatment response in glioblastoma: multicentre application of a novel pipeline incorporating bioinformatics and machine learning
Authors
Waqar, M.Hessen, E.
van Houdt, P.
Lewis, D.
Li, K.
Zhu, X.
Jackson, A.
Iqbal, M.
van der Heide, U. A.
Coope, D.
Borst, Gerben R
Affiliation
The Christie NHS Foundation Trust, Manchester, United KingdomIssue Date
2024
Metadata
Show full item recordCitation
Waqar M, Hessen E, van Houdt P, Lewis D, Li K, Zhu X, et al. IMAGING HABITATS CAN PREDICT EARLY PROGRESSION AND CHARACTERISE TREATMENT RESPONSE IN GLIOBLASTOMA: MULTICENTRE APPLICATION OF A NOVEL PIPELINE INCORPORATING BIOINFORMATICS AND MACHINE LEARNING. Neuro-oncology. 2024 OCT 17;26:V52-V. PubMed PMID: WOS:001340502000169. English.Journal
Neuro-OncologyDOI
10.1093/neuonc/noae144.169Additional Links
https://dx.doi.org/10.1093/neuonc/noae144.169Type
Meetings and ProceedingsLanguage
enae974a485f413a2113503eed53cd6c53
10.1093/neuonc/noae144.169