Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia

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Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia

Purpose The purpose of this study is to investigate whether machine learning with dosiomic, radiomic, and demographic features allows for xerostomia risk assessment more precise than normal tissue complication probability (NTCP) models based on the mean radiation dose to parotid glands. Material and methods A cohort of 153 head-and-neck cancer patients was used to model xerostomia at 0-6 mont...

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ژورنال

عنوان ژورنال: Frontiers in Oncology

سال: 2018

ISSN: 2234-943X

DOI: 10.3389/fonc.2018.00035