MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring
The adoption of Large Language Models for radiology report structuring has been largely dominated by either proprietary cloud-based models or large open models requiring high-end GPUs for deployment, which is a critical bottleneck for clinical adoption in radiology workflows that demand data privacy and offline operation. To address this, we present MedPAO-Assist, an edge-deployable agentic framework that generates structured radiology reports directly from radiologist dictation and voice commands, requiring only $\approx3.3$ GB peak RAM and achieving an average end-to-end latency of $\approx31$ seconds on a standard laptop CPU through an asynchronous, multi-threaded execution pipeline. T...
| Authors | Shrish Shrinath Vaidya, Minmini Selvam, Ganapathy Krishnamurthi |
|---|---|
| Primary category | cs.AI |
| Published | 17 October 2026 |
| Last updated at source | 17 October 2026 |
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