相关实验视频

Updated: Sep 16, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

587

从生物医学BERT模型中嵌入的参数知识中预测药物副作用关系:使用自然语言处理方法进行方法学研究

Woohyuk Jeon1, Minjae Park1, Doyeon An1

  • 1Department of Computer Engineering, College of IT Convergence, Gachon University, AI·Engineering Building, 317A, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Seongnam, 13120, Republic of Korea, 82 010-9012-9364, 82 031-750-5333.

JMIR medical informatics
|July 10, 2025
PubMed
概括

这项研究引入了一种使用生物医学BERT模型来预测未知的药物副作用关系的新方法,其性能优于传统模型. 该方法在管理药物不良反应方面表现出高准确性和实际适用性.

关键词:
预测ADR的预测贝尔特 (BERT) 公司来自变压器的双向编码器表示在NLP中,我们使用了NLP.药物不良反应 药物不良反应药物副作用关系关系 药物副作用关系自然语言处理自然语言处理.一个词嵌入的词嵌入.

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