Hochschulschrift
Machine learning using radiomics and dosiomics for normal tissue complication probability modeling of radiation-induced xerostomia
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Maße
-
30 cm
- Umfang
-
iv, 120 Seiten
- Sprache
-
Englisch
- Anmerkungen
-
Illustrationen, Diagramme
Ruprecht-Karls-Universität Heidelberg, Dissertation, 2019
- Schlagwort
-
ntcp
radiotherapy
machine
learning
- Inhaltsverzeichnis
- Rechteinformation
-
Bei diesem Objekt liegt nur das Inhaltsverzeichnis digital vor. Der Zugriff darauf ist unbeschränkt möglich.
- Letzte Aktualisierung
-
11.06.2025, 13:40 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Hochschulschrift
Beteiligte
Entstanden
- 2018
Ähnliche Objekte (12)
Machine learning using radiomics and dosiomics for normal tissue complication probability modeling of radiation-induced xerostomia
Development of a normal tissue complication probability (NTCP) model for radiation-induced hypothyroidism in nasopharyngeal carcinoma patients
Normal tissue complication probability modelling : influence of treatment technique, fractionation, and dose calculation algorithm
Definition of an Normal Tissue Complication Probability Model for the Inner Ear in Definitive Radiochemotherapy of Nasopharynx Carcinoma
Definition of an normal tissue complication probability model for the inner ear in definitive radiochemotherapy of nasopharynx carcinoma
Influence of urethra sparing on tumor control probability and normal tissue complication probability in focal dose escalated hypofractionated radiotherapy: A planning study based on histopathology reference
Radiomics risk modelling using machine learning algorithms for personalised radiation oncology
Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis
AutoRadiomics: a framework for reproducible radiomics research
Development of Machine Learning-based Spatially and Temporally Resolved 4D Radiomics in Radiation Oncology
Grande Complication No 42500
Ueber Harmonie und Complication
Machine learning using radiomics and dosiomics for normal tissue complication probability modeling of radiation-induced xerostomia
Development of a normal tissue complication probability (NTCP) model for radiation-induced hypothyroidism in nasopharyngeal carcinoma patients
Normal tissue complication probability modelling : influence of treatment technique, fractionation, and dose calculation algorithm
Definition of an Normal Tissue Complication Probability Model for the Inner Ear in Definitive Radiochemotherapy of Nasopharynx Carcinoma
Definition of an normal tissue complication probability model for the inner ear in definitive radiochemotherapy of nasopharynx carcinoma
Influence of urethra sparing on tumor control probability and normal tissue complication probability in focal dose escalated hypofractionated radiotherapy: A planning study based on histopathology reference
Radiomics risk modelling using machine learning algorithms for personalised radiation oncology
Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis
AutoRadiomics: a framework for reproducible radiomics research
Development of Machine Learning-based Spatially and Temporally Resolved 4D Radiomics in Radiation Oncology
Grande Complication No 42500
Ueber Harmonie und Complication
Machine learning using radiomics and dosiomics for normal tissue complication probability modeling of radiation-induced xerostomia
Development of a normal tissue complication probability (NTCP) model for radiation-induced hypothyroidism in nasopharyngeal carcinoma patients
Normal tissue complication probability modelling : influence of treatment technique, fractionation, and dose calculation algorithm
Definition of an Normal Tissue Complication Probability Model for the Inner Ear in Definitive Radiochemotherapy of Nasopharynx Carcinoma
Definition of an normal tissue complication probability model for the inner ear in definitive radiochemotherapy of nasopharynx carcinoma
Influence of urethra sparing on tumor control probability and normal tissue complication probability in focal dose escalated hypofractionated radiotherapy: A planning study based on histopathology reference
Radiomics risk modelling using machine learning algorithms for personalised radiation oncology
Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis
AutoRadiomics: a framework for reproducible radiomics research
Development of Machine Learning-based Spatially and Temporally Resolved 4D Radiomics in Radiation Oncology
Grande Complication No 42500