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Updated: Jan 13, 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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预测部分观察到的长期结果与对抗性积极的未标记的域名适应

Mengying Yan1, Meng Xia2, Wei A Huang1

  • 1Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA; Duke AI Health, Duke University School of Medicine, Durham, NC, USA.

Proceedings of machine learning research
|January 9, 2026
PubMed
概括

这项研究引入了一种新的电子健康记录 (EHR) 领域适应方法,以预测长期结果. 该方法有效地将历史数据适应当代患者队列,提高预测准确性.

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