تحميل...

Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy

BACKGROUND AND PURPOSE: Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatial dose metrics and machine learning. MATERIAL AND...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
الحاوية / القاعدة:	Radiother Oncol
المؤلفون الرئيسيون:	Dean, Jamie A, Wong, Kee H, Welsh, Liam C, Jones, Ann-Britt, Schick, Ulrike, Newbold, Kate L, Bhide, Shreerang A, Harrington, Kevin J, Nutting, Christopher M, Gulliford, Sarah L
التنسيق:	Artigo
اللغة:	Inglês
منشور في:	2016
الموضوعات:	Article
الوصول للمادة أونلاين:	https://ncbi.nlm.nih.gov/pmc/articles/PMC5021201/ https://ncbi.nlm.nih.gov/pubmed/27240717 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.radonc.2016.05.015
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Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy

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