FollowUpBot: An LLM-Based Conversational Robot for Automatic Postoperative Follow-up

TL;DR

FollowUpBot is an innovative LLM-powered robot designed for dynamic, private, and automated postoperative patient follow-up, improving efficiency and accuracy in recovery monitoring.

Contribution

The paper introduces FollowUpBot, a novel edge-deployed LLM-based robot that enables adaptive face-to-face postoperative follow-up and automatic report generation.

Findings

High patient coverage and satisfaction.

Accurate report generation across diverse cases.

Effective privacy-preserving interactions.

Abstract

Postoperative follow-up plays a crucial role in monitoring recovery and identifying complications. However, traditional approaches, typically involving bedside interviews and manual documentation, are time-consuming and labor-intensive. Although existing digital solutions, such as web questionnaires and intelligent automated calls, can alleviate the workload of nurses to a certain extent, they either deliver an inflexible scripted interaction or face private information leakage issues. To address these limitations, this paper introduces FollowUpBot, an LLM-powered edge-deployed robot for postoperative care and monitoring. It allows dynamic planning of optimal routes and uses edge-deployed LLMs to conduct adaptive and face-to-face conversations with patients through multiple interaction modes, ensuring data privacy. Moreover, FollowUpBot is capable of automatically generating structured postoperative follow-up reports for healthcare institutions by analyzing patient interactions during follow-up. Experimental results demonstrate that our robot achieves high coverage and satisfaction in follow-up interactions, as well as high report generation accuracy across diverse field types. The demonstration video is available at https://www.youtube.com/watch?v=_uFgDO7NoK0.