Cluster model incorporating heterogeneous dose distribution of partial parotid irradiation for radiotherapy induced xerostomia prediction with machine learning methods-Reference-Cited by-同舟云学术

Cluster model incorporating heterogeneous dose distribution of partial parotid irradiation for radiotherapy induced xerostomia prediction with machine learning methods

Published:2022-05-09 Issue:7 Volume:61 Page:842-848
ISSN:0284-186X
Container-title:Acta Oncologica
language:en
Short-container-title:Acta Oncologica

Author:

Chao Ming¹,El Naqa Issam²³,Bakst Richard L.¹,Lo Yeh-Chi¹,Peñagarícano José A.³

Affiliation:

1. Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, The Mount Sinai Hospital, New York, NY, USA

2. Department of Machine Learning, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA

3. Department of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA

Publisher

Informa UK Limited

Subject

Radiology, Nuclear Medicine and imaging,Oncology,Hematology,General Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/0284186X.2022.2073187

Reference33 articles.

1. Radiotherapy Dose–Volume Effects on Salivary Gland Function

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

3. Parotid gland mean dose as a xerostomia predictor in low-dose domains

4. Dose–volume modeling of salivary function in patients with head-and-neck cancer receiving radiotherapy

5. NTCP models for patient-rated xerostomia and sticky saliva after treatment with intensity modulated radiotherapy for head and neck cancer: The role of dosimetric and clinical factors

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