Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.8K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Successful transcatheter closure of a large inferior sinus venosus atrial septal defect.

Pediatrics and neonatology·2025
Same author

The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII.

Database : the journal of biological databases and curation·2024
Same author

Intraperitoneal Corticosteroid Injection for Refractory Ascites in a Patient with Fontan Circulation.

Acta Cardiologica Sinica·2024
Same author

Surveying biomedical relation extraction: a critical examination of current datasets and the proposal of a new resource.

Briefings in bioinformatics·2024
Same author

Hepatorenal Syndrome in Fontan Circulation with Atypical Hemodynamic Presentation.

Acta Cardiologica Sinica·2023
Same author

Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition.

Database : the journal of biological databases and curation·2023

相关实验视频

Updated: May 2, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.6K

通过以数据为中心和预处理强大的集体学习方法加强生物医学关系提取.

Wilailack Meesawad1, Jen-Chieh Han1, Chun-Yu Hsueh1

  • 1Department of Computer Science and Information Engineering, National Central University, No. 300, Zhongda Rd., Zhongli District, Taoyuan 320, Taiwan.

Database : the journal of biological databases and curation
|May 22, 2025
PubMed
概括

本研究介绍了一个生物医学关系提取系统,使用集体学习和BERT模型进行文献分析. 该方法实现了卓越的性能,为关系提取任务建立了新的基准.

更多相关视频

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

2.3K
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

1.7K

相关实验视频

Last Updated: May 2, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.6K
A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

2.3K
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

1.7K

科学领域:

  • 生物医学信息学 生物医学信息学
  • 自然语言处理自然语言处理.
  • 机器学习 机器学习

背景情况:

  • 生物医学关系提取对于从文献中理解复杂的生物信息至关重要.
  • 现有系统在准确识别生物医学实体之间的关系方面面临挑战.

研究的目的:

  • 开发和评估一个新的生物医学关系提取系统,以应对BioCreative VIII挑战.
  • 建立一个可靠的基准来评估生物医学文本中的关系提取性能.

主要方法:

  • 利用集体学习方法,将多个预训练的双向编码器表示从变压器 (BERT) 模型中结合起来,包括PubMedBERT.
  • 集成的预处理技术,如提示性问题,实体ID对,同时发生的上下文,特殊令牌和边界标签.
  • 采用马克斯规则整体学习机制来汇总来自各种分类器的输出.

主要成果:

  • 开发的系统超过了生物医学关系提取的标准得分.
  • 证明了以数据为中心的方法在提高模型性能和稳定性的有效性.

结论:

  • 拟议的集体学习系统为生物医学关系提取提供了高性能解决方案.
  • 优先考虑高质量的数据对于提高关系提取模型的性能和稳定性至关重要.