Autonomous radiotherapy planning via agentic orchestration using a multimodal TPS-integrated compound AI platform

Purpose. Radiation therapy (RT) treatment planning requires iterative, multi-day optimization workflows in which subjective planning strategies produce inter-planner variability in plan quality. Existing computational approaches automate isolated aspects of this workflow, yet none orchestrates an en...

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Principais autores:	Austen Matthew Maniscalco, Yang Kyun Park, Sean J Domal, Mu-Han Lin, Sanda Harabagiu, Steve B Jiang, Dan Nguyen
Formato:	Artigo
Idioma:	Inglês
Publicado:	IOP Publishing 2026-01-01
Series:	Machine Learning: Health
Assuntos:	autonomous treatment planning radiation therapy dose prediction compound AI systems LLM agents multi-agent orchestration
Acceso en liña:	https://doi.org/10.1088/3049-477X/ae7978
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