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Updated: Sep 13, 2025

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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评估医学编码和医院再接收风险分层的大型语言模型的推理能力:零射击促使方法

Parvati Naliyatthaliyazchayil1, Raajitha Muthyala1, Judy Wawira Gichoya2

  • 1Department of Biomedical Engineering and Informatics, Luddy School of Informatics, Computing and Engineering, Indiana University Indianapolis, 535 W Michigan Street, Indianapolis, IN, 46202, United States, 1 317 274 0439.

Journal of medical Internet research
|July 30, 2025
PubMed
概括

大型语言模型在零射击临床诊断和风险预测方面表现出适度的成功,但在医学编码方面存在困难. 特定任务的微调和人类监督对于可靠的医疗保健应用程序至关重要.

关键词:
临床决策支持 临床决策支持可以解释性的解释性.大型语言模型.医学编码 医学编码主要诊断 预测 预测再接收风险预测和预测零射击学习的学习

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