Feasibility study of automatic radiotherapy treatment planning for cervical cancer using a large language model

Abstract Background Radiotherapy treatment planning traditionally involves complex and time-consuming processes, often relying on trial-and-error methods. The emergence of artificial intelligence, particularly Large Language Models (LLMs), surpassing human capabilities and existing algorithms in var...

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Principais autores:	Shuoyang Wei, Ankang Hu, Yongguang Liang, Jingru Yang, Lang Yu, Wenbo Li, Bo Yang, Jie Qiu
Format:	Artigo
Jezik:	Inglês
Izdano:	BMC 2025-05-01
Serija:	Radiation Oncology
Teme:	Radiotherapy Treatment planning Large language model Automation
Online dostop:	https://doi.org/10.1186/s13014-025-02660-5
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