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Research progress on application of machine learning in quality assurance of intensity-modulated radiotherapy / 中华放射肿瘤学杂志
Chinese Journal of Radiation Oncology ; (6): 309-313, 2019.
Artigo em Chinês | WPRIM | ID: wpr-745301
ABSTRACT
In recent years,the application of machine learning in the field of radiotherapy has been gradually increased along with the development of big data and artificial intelligence technology.Through the training of previous plans,machine learning can predict the results of plan quality and dose verification.It can also predict the multi-leaf collimator (MLC) positioning error and linear accelerator performance.In addition,machine learning can be applied in the quality assurance of intensity-modulated radiotherapy to improve the quality and efficiency of treatment plan and implementation,increase the benefits to the patients and reduce the risk.However,there are many problems,such as difficulty in the selection,extraction and calculation of characteristic value,requirement for large training sample size and insufficient prediction accuracy,which impede its clinical translation and application.In this article,research progress on the application of machine learning in the quality assurance of IMRT was reviewed.

Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Tipo de estudo: Estudo prognóstico Idioma: Chinês Revista: Chinese Journal of Radiation Oncology Ano de publicação: 2019 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Tipo de estudo: Estudo prognóstico Idioma: Chinês Revista: Chinese Journal of Radiation Oncology Ano de publicação: 2019 Tipo de documento: Artigo