Multitask Learning with Convolutional Neural Networks and Vision Transformers Can Improve Outcome Prediction for Head and Neck Cancer Patients

SIMPLE SUMMARY: Increasing treatment efficacy for head and neck cancer requires the utilization of patient-specific biomarkers to personalize therapy. Deep neural networks show promise for extracting prognostic biomarkers from medical imaging data to predict loco-regional tumor recurrence or disease...

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Detalles Bibliográficos
Autores principales: Starke, Sebastian, Zwanenburg, Alex, Leger, Karoline, Lohaus, Fabian, Linge, Annett, Kalinauskaite, Goda, Tinhofer, Inge, Guberina, Nika, Guberina, Maja, Balermpas, Panagiotis, von der Grün, Jens, Ganswindt, Ute, Belka, Claus, Peeken, Jan C., Combs, Stephanie E., Boeke, Simon, Zips, Daniel, Richter, Christian, Troost, Esther G. C., Krause, Mechthild, Baumann, Michael, Löck, Steffen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571894/
https://www.ncbi.nlm.nih.gov/pubmed/37835591
http://dx.doi.org/10.3390/cancers15194897

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571894/
https://www.ncbi.nlm.nih.gov/pubmed/37835591
http://dx.doi.org/10.3390/cancers15194897

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