相关实验视频

Updated: Jan 9, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

994

增加大型语言模型,以利用患者临床笔记预测阿片类药物使用障碍中精神健康的社会决定因素

Madhavi Pagare1, Deva Sai Kumar Bheesetti1, Inyene Essien-Aleksi2

  • 1Cognitive Ubiquitous Computing and System (CUBICS) Lab, University of Massachusetts Lowell, Lowell, MA 01854, United States.

JAMIA open
|December 1, 2025
PubMed
概括

这项研究引入了一个新的框架 (HLLIA) 和算法 (MHCLE) 来从临床笔记中准确识别阿片类药物使用障碍患者的心理健康的社会决定因素,改进早期干预策略.

关键词:
人类在循环中的LLM互动用于注释 (HLLIA)多层次层次临床-长型嵌入式 (MHCLE)自然语言处理 (NLP)"阿片类药物使用障碍"与阿片类药物相关的结果心理健康的社会决定因素 (SDOMH)

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