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Incorporating spatial dose metrics in machine learning-based normal tissue complication probability (NTCP) models of severe acute dysphagia resulting from head and neck radiotherapy
Severe acute dysphagia commonly results from head and neck radiotherapy (RT). A model enabling prediction of severity of acute dysphagia for individual patients could guide clinical decision-making. Statistical associations between RT dose distributions and dysphagia could inform RT planning protoco...
Autores principales: | Dean, Jamie, Wong, Kee, Gay, Hiram, Welsh, Liam, Jones, Ann-Britt, Schick, Ulricke, Oh, Jung Hun, Apte, Aditya, Newbold, Kate, Bhide, Shreerang, Harrington, Kevin, Deasy, Joseph, Nutting, Christopher, Gulliford, Sarah |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5796681/ https://www.ncbi.nlm.nih.gov/pubmed/29399642 http://dx.doi.org/10.1016/j.ctro.2017.11.009 |
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