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.

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2018 nî lūn-bûn

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2018年の論文

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

@zh-my

2018年学术文章

@zh-sg

2018年學術文章

@yue

2018年學術文章

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2018年學術文章

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Design and Selection of Machin ...... bility Modeling of Xerostomia.

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Design and Selection of Machin ...... bility Modeling of Xerostomia.

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Item

label

Design and Selection of Machin ...... bility Modeling of Xerostomia.

@en

Design and Selection of Machin ...... bility Modeling of Xerostomia.

@nl

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Design and Selection of Machin ...... bility Modeling of Xerostomia.

@en

Design and Selection of Machin ...... bility Modeling of Xerostomia.

@nl

P1476

Design and Selection of Machin ...... bility Modeling of Xerostomia.

@en

P2093

Florian Buettner

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Florian Sterzing

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Henrik Hauswald

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Hubert S Gabryś

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Mark Bangert

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P2860

The meaning and use of the area under a receiver operating characteristic (ROC) curve

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Investigation of the support vector machine algorithm to predict lung radiation-induced pneumonitis

Novel approaches to improve the therapeutic index of head and neck radiotherapy: an analysis of data from the PARSPORT randomised phase III trial.

Using multivariate regression model with least absolute shrinkage and selection operator (LASSO) to predict the incidence of Xerostomia after intensity-modulated radiotherapy for head and neck cancer.

Patient- and therapy-related factors associated with the incidence of xerostomia in nasopharyngeal carcinoma patients receiving parotid-sparing helical tomotherapy.

Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer.

Normal Tissue Complication Probability (NTCP) Modelling of Severe Acute Mucositis using a Novel Oral Mucosal Surface Organ at Risk.

Prediction error estimation: a comparison of resampling methods.

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scholarly article

P356

10.3389/FONC.2018.00035

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P478

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P577

2018-03-05T00:00:00Z

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P698

29556480

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P921

machine learning

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5844945

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