English(EN) TAMA: A Human-AI Collaborative Thematic Analysis Framework Using Multi-Agent LLMs for Clinical Interviews

AI框架TAMA增强临床访谈主题分析

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-07 04:00

研究人员开发了TAMA，一个使用多智能体大语言模型（LLMs）辅助临床访谈主题分析的新框架。这种人机协作方法旨在简化医疗保健领域中资源密集型的定性数据分析过程。在分析患有罕见先天性心脏病的儿童父母的访谈记录时，TAMA在主题准确性和覆盖率方面均优于单智能体LLM方法。 AI

影响该框架可以显著减轻临床环境中定性数据分析的 manual workload，从而可能加速研究并改善对患者护理的洞察。

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arXiv cs.CL TIER_1 English(EN) · Huimin Xu, Seungjun Yi, Terence Lim, Jiawei Xu, Andrew Well, Carlos Mery, Aidong Zhang, Yuji Zhang, Heng Ji, Keshav Pingali, Yan Leng, Ying Ding · 2026-07-07 04:00

TAMA：一种使用多代理LLM进行临床访谈的人工智能协作主题分析框架

arXiv:2503.20666v2 Announce Type: replace-cross Abstract: Thematic analysis (TA) is a widely used qualitative approach for uncovering latent meanings in unstructured text data. TA provides valuable insights in healthcare but is resource-intensive. Large Language Models (LLMs) hav…