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NIMG-67. DEVELOPMENT OF VERSATILE MACHINE-LEARNING APPROACHES FOR RADIOGENOMICS OF GLIOMA IN DIFFERENT COHORTS

BACKGROUND: Radiogenomics aims to analyze clinical images and information, and to predict key molecular profiles of tumors. However, imaging protocol is usually different in facilities, and it has been rarely examined whether the performance of developed methods in a dataset is robustly sustained ev...

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Bibliografische gegevens
Gepubliceerd in:Neuro Oncol
Hoofdauteurs: Takahashi, Masamichi, Kawaguchi, Risa, Takahashi, Satoshi, Miyake, Mototaka, Kinoshita, Manabu, Ichimura, Koichi, Hamamoto, Ryuji, Narita, Yoshitaka, Sese, Jun
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Oxford University Press 2019
Onderwerpen:
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6847293/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/neuonc/noz175.736
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