Incorporating spatial dose metrics in machine learning-based normal tissue complication probability (NTCP) models of severe acute dysphagia resulting from head and neck radiotherapy

Gelijkaardige items

• 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
  door: Dean, Jamie A, et al.
  Gepubliceerd in: (2016)
• Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy
  door: Dean, Jamie A., et al.
  Gepubliceerd in: (2016)
• Brain-Sparing Methods for IMRT of Head and Neck Cancer
  door: Dunlop, Alex, et al.
  Gepubliceerd in: (2015)
• Normal Tissue Complication Probability (NTCP) modeling of late rectal bleeding following external beam radiotherapy for prostate cancer: A Test of the QUANTEC-recommended NTCP model
  door: Liu, Mitchell, et al.
  Gepubliceerd in: (2010)
• Practice patterns for the radical treatment of nasopharyngeal cancer by head and neck oncologists in the United Kingdom
  door: Petkar, Imran, et al.
  Gepubliceerd in: (2018)