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Updated: May 30, 2025

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

Published on: December 6, 2024

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在电子健康记录中对心理健康预测模型进行非结构化文本的分类:大型语言模型评估研究

Nicholas C Cardamone1, Mark Olfson2, Timothy Schmutte3

  • 1Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

JMIR medical informatics
|January 26, 2025
PubMed
概括

大型语言模型 (LLM) 显示了与临床医生在电子健康记录 (EHR) 术语分类方面的高度一致. 虽然LLM为预测模型的手动编码提供了有希望的替代方案,但在对特定的心理和身体健康术语进行分类方面存在差异.

关键词:
在这里,我们可以看到AIAIAI.聊天GPT 聊天GPT 聊天欧洲人权理事会 欧洲人权理事会欧洲人机系统系统的EHR系统.在法学士 (LLM) 课程中.ML ML 在 ML在NLP中,我们使用了NLP.人工智能的人工智能是人工智能.数据集数据集数据集电子健康记录 电子健康记录紧急情况部门的急救部门.医疗信息学 医疗信息学大型语言模型机器学习是机器学习.心理健康 心理健康精神健康障碍 精神健康障碍自然语言处理自然语言处理.身体健康 身体健康 身体健康预测建模预测建模文本 文本 文本

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