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LLM orchestrates AI workflows for radiotherapy care pathway

By PulseAugur Editorial · [1 sources] ·

Researchers have developed RadOnc-Agent, a framework that uses a large language model to orchestrate AI workflows across the radiotherapy care pathway. This system formalizes radiotherapy into four clinical phases and provides 26 callable functions through a conversational interface. Evaluations showed high success rates in selecting intended functions and completing synthetic and real-patient workflows, highlighting the feasibility of LLM-orchestrated architectures for coordinating complex medical processes. AI

IMPACT Demonstrates LLM orchestration capabilities for complex, multi-stage medical workflows, potentially improving efficiency and integration in healthcare.

RANK_REASON The item is a research paper detailing a new AI framework. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM orchestrates AI workflows for radiotherapy care pathway

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The item is a research paper detailing a new AI framework. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Caiwen Jiang, Shuoyang Wei, Songlin Zhao, Junyu Li, Jingyuan Chen, Wei Liu ·

    RadOnc-Agent: An LLM-Orchestrated Framework for AI Workflows Across the Radiotherapy Care Pathway

    arXiv:2610.06923v1 Announce Type: new Abstract: Artificial intelligence has advanced individual radiotherapy tasks, yet these capabilities remain separated across clinical stages, software environments and data modalities. This fragmentation contrasts with the longitudinal radiot…

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