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English(EN) LLM-MINE: Large Language Model based Alzheimer's Disease and Related Dementias Phenotypes Mining from Clinical Notes

LLM-MINE框架从临床笔记中提取阿尔茨海默病表型

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了LLM-MINE，一个利用大语言模型从临床笔记中提取阿尔茨海默病及相关痴呆症（ADRD）表型的框架。该方法旨在通过分析电子健康记录中的非结构化文本来改善早期检测和疾病分期。与传统的生物医学命名实体识别（NER）和基于字典的方法相比，LLM-MINE框架，特别是使用结合了表型列表的少样本提示时，在识别具有统计学意义的表型差异和无监督疾病分期方面表现出更优越的性能。 AI

影响 这项研究展示了大语言模型从非结构化医疗数据中挖掘具有临床意义的信号的潜力，可能改善疾病诊断和分期。

排序理由 该集群包含一篇学术论文，详细介绍了使用大语言模型进行表型提取的新框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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LLM-MINE框架从临床笔记中提取阿尔茨海默病表型

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该集群包含一篇学术论文，详细介绍了使用大语言模型进行表型提取的新框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mingchen Shao, Yuzhang Xie, Carl Yang, Jiaying Lu ·

    LLM-MINE：基于大型语言模型的临床笔记阿尔茨海默病及相关痴呆症表型挖掘

    arXiv:2603.13673v2 Announce Type: replace Abstract: Accurate extraction of Alzheimer's Disease and Related Dementias (ADRD) phenotypes from electronic health records (EHR) is critical for early-stage detection and disease staging. However, this information is usually embedded in …

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