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Updated: Feb 18, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

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将临床叙述和结构化表型与大型语言模型和句子转换器相结合

Jihao Cai1, Guozhuang Li1, Yongxin Yang2

  • 1Department of Orthopaedic Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; Beijing Key of Big Data Innovation and Application for Skeletal Health Medical Care, Beijing, 100730, China; Key Laboratory of Big Data for Spinal Deformities, Chinese Academy of Medical Sciences, Beijing, 100730, China.

Journal of genetics and genomics = Yi chuan xue bao
|February 16, 2026
PubMed
概括

我们开发了LEAP (LLM-Enhanced Automated Phenotyping),这是一个用于从电子健康记录中提取结构化表型的新框架. LEAP显著提高了用于遗传研究和临床应用的表型数据的准确性和可靠性.

关键词:
电子健康记录是电子健康记录.人类现象型的本体学.大型语言模型.门德尔的障碍 门德尔的障碍 门德尔的障碍句子变换器 句子变换器

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