Verfügbarkeit: PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas

PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas:

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Bibliographische Detailangaben
1. Verfasser:	Haider, Stefan Philipp Markus 1996- (VerfasserIn)
Format:	Abschlussarbeit Buch
Sprache:	English
Veröffentlicht:	München 2023
Schlagworte:	Krebs > Medizin Bildgebendes Verfahren Positronen-Emissions-Tomografie Computertomografie Hochschulschrift
Online-Zugang:	Volltext Volltext
Beschreibung:	91 Blätter Illustrationen
DOI:	10.5282/edoc.31714

Internformat

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spelling	Haider, Stefan Philipp Markus 1996- Verfasser (DE-588)1291619267 aut PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas Stefan Philipp Markus Haider München 2023 91 Blätter Illustrationen txt rdacontent n rdamedia nc rdacarrier Dissertation München, Ludwig-Maximilians-Universität 2023 3\p Krebs Medizin (DE-588)4073781-0 gnd 4\p Bildgebendes Verfahren (DE-588)4006617-4 gnd 5\p Positronen-Emissions-Tomografie (DE-588)4129799-4 gnd 6\p Computertomografie (DE-588)4113240-3 gnd (DE-588)4113937-9 Hochschulschrift gnd-content Erscheint auch als Online-Ausgabe urn:nbn:de:bvb:19-317139 10.5282/edoc.31714 https://doi.org/10.5282/edoc.31714 Verlag kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bvb:19-317139 Resolving-System kostenfrei Volltext 1\p emakn 0,43684 20230606 DE-101 https://d-nb.info/provenance/plan#emakn 2\p emasg 0,90514 20230606 DE-101 https://d-nb.info/provenance/plan#emasg 3\p emagnd 0,19706 20230606 DE-101 https://d-nb.info/provenance/plan#emagnd 4\p emagnd 0,07931 20230606 DE-101 https://d-nb.info/provenance/plan#emagnd 5\p emagnd 0,07390 20230606 DE-101 https://d-nb.info/provenance/plan#emagnd 6\p emagnd 0,05316 20230606 DE-101 https://d-nb.info/provenance/plan#emagnd
spellingShingle	Haider, Stefan Philipp Markus 1996- PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas 3\p Krebs Medizin (DE-588)4073781-0 gnd 4\p Bildgebendes Verfahren (DE-588)4006617-4 gnd 5\p Positronen-Emissions-Tomografie (DE-588)4129799-4 gnd 6\p Computertomografie (DE-588)4113240-3 gnd
subject_GND	(DE-588)4073781-0 (DE-588)4006617-4 (DE-588)4129799-4 (DE-588)4113240-3 (DE-588)4113937-9
title	PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas
title_auth	PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas
title_exact_search	PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas
title_exact_search_txtP	PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas
title_full	PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas Stefan Philipp Markus Haider
title_fullStr	PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas Stefan Philipp Markus Haider
title_full_unstemmed	PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas Stefan Philipp Markus Haider
title_short	PET/CT radiomics and machine learning for non-invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas
title_sort	pet ct radiomics and machine learning for non invasive molecular and prognostic characterization of oropharyngeal squamous cell carcinomas
topic	3\p Krebs Medizin (DE-588)4073781-0 gnd 4\p Bildgebendes Verfahren (DE-588)4006617-4 gnd 5\p Positronen-Emissions-Tomografie (DE-588)4129799-4 gnd 6\p Computertomografie (DE-588)4113240-3 gnd
topic_facet	Krebs Medizin Bildgebendes Verfahren Positronen-Emissions-Tomografie Computertomografie Hochschulschrift
url	https://doi.org/10.5282/edoc.31714 https://nbn-resolving.org/urn:nbn:de:bvb:19-317139
work_keys_str_mv	AT haiderstefanphilippmarkus petctradiomicsandmachinelearningfornoninvasivemolecularandprognosticcharacterizationoforopharyngealsquamouscellcarcinomas

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