Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinoma

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinoma ; volume:14 ; number:1 ; day:5 ; month:1 ; year:2024 ; pages:1-11 ; date:12.2024
Scientific reports ; 14, Heft 1 (5.1.2024), 1-11, 12.2024

Creator: Schön, Felix
Kieslich, Aaron
Nebelung, Heiner
Riediger, Carina
Hoffmann, Ralf-Thorsten
Zwanenburg, Alex
Löck, Steffen
Kühn, Jens-Peter

Contributor: SpringerLink (Online service)

DOI: 10.1038/s41598-023-50451-3

URN: urn:nbn:de:101:1-2024031821234988676445

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:44 AM CEST

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Schön, Felix
Kieslich, Aaron
Nebelung, Heiner
Riediger, Carina
Hoffmann, Ralf-Thorsten
Zwanenburg, Alex
Löck, Steffen
Kühn, Jens-Peter
SpringerLink (Online service)

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Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinoma

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Other Objects (12)

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Non-resonant background removal in broadband CARS microscopy using deep-learning algorithms

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Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy

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