Characterizing the interplay of treatment parameters and complexity and their impact on performance on an IROC IMRT phantom using machine learning-Reference-Cited by-同舟云学术

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Characterizing the interplay of treatment parameters and complexity and their impact on performance on an IROC IMRT phantom using machine learning

Published:2023-05 Issue: Volume:182 Page:109577
ISSN:0167-8140
Container-title:Radiotherapy and Oncology
language:en
Short-container-title:Radiotherapy and Oncology

Author:

Mehrens Hunter,Molineu Andrea,Hernandez Nadia,Court Laurence,Howell Rebecca,Jaffray David,Peterson Christine B.,Pollard-Larkin Julianne,Kry Stephen F.

Funder

National Institutes of Health

National Cancer Institute

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Oncology,Hematology

Reference34 articles.

1. Head and neck cancer;Chow;N Engl J Med,2020

2. Recurrence patterns after IMRT/VMAT in head and neck cancer;Bollen;Front Oncol,2021

3. Examining credentialing criteria and poor performance indicators for IROC Houston's anthropomorphic head and neck phantom;Carson;Med Phys,2016

4. Survey results of 3D-CRT and IMRT quality assurance practice;Mehrens;J Appl Clin Med Phys,2020

5. On the sensitivity of TG-119 and IROC credentialing to TPS commissioning errors;McVicker;J Appl Clin Med Phys,2016

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1. Incorporating plan complexity into the statistical process control of volumetric modulated arc therapy pre‐treatment verifications;Medical Physics;2024-04-17

2. Radiotherapy dosimetry at multiple levels to improve precision, development and understanding of treatment;Radiotherapy and Oncology;2023-05

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