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Assessing Versatile Machine Learning Models for Glioma Radiogenomic Studies across Hospitals

SIMPLE SUMMARY: Radiogenomics enables prediction of the status and prognosis of patients using non-invasively obtained imaging data. Current machine learning (ML) methods used in radiogenomics require huge datasets, which involve the handling of large heterogeneous datasets from multiple cohorts/hos...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Veröffentlicht in:Cancers (Basel)
Hauptverfasser: Kawaguchi, Risa K., Takahashi, Masamichi, Miyake, Mototaka, Kinoshita, Manabu, Takahashi, Satoshi, Ichimura, Koichi, Hamamoto, Ryuji, Narita, Yoshitaka, Sese, Jun
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI 2021
Schlagworte:
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC8306149/
https://ncbi.nlm.nih.gov/pubmed/34298824
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/cancers13143611
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