Longitudinal and Multimodal Radiomics Models for Head and Neck Cancer Outcome Prediction

SIMPLE SUMMARY: Machine learning based radiomics models for prediction of loco-regional recurrence today mostly rely on features extracted from pre-treatment imaging data. In this work, we investigate the predictive ability of such models when imaging data obtained during the course of treatment are...

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Detalles Bibliográficos
Autores principales: Starke, Sebastian, Zwanenburg, Alexander, Leger, Karoline, Zöphel, Klaus, Kotzerke, Jörg, Krause, Mechthild, Baumann, Michael, Troost, Esther G. C., Löck, Steffen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913206/
https://www.ncbi.nlm.nih.gov/pubmed/36765628
http://dx.doi.org/10.3390/cancers15030673

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913206/
https://www.ncbi.nlm.nih.gov/pubmed/36765628
http://dx.doi.org/10.3390/cancers15030673

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