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

Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

218
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
218
Natural and Artificial Concepts01:24

Natural and Artificial Concepts

545
In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
545
Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

11.7K
The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...
11.7K

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

Spherical adsorptive carbon use and risks of dialysis initiation and mortality in advanced chronic kidney disease: a real-world cohort study.

Kidney research and clinical practice·2026
Same author

Orchestrator multi-agent clinical decision support system for secondary headache diagnosis in primary care.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

Implementing trust in non-small cell lung cancer diagnosis with a conformalized uncertainty-aware AI framework.

Nature biomedical engineering·2026
Same author

Generating synthetic multi-national longitudinal cohorts for clinically grounded HIV research.

Nature communications·2026
Same author

A real-world feasibility evaluation of LLM-based clinical prediction: emergency department return visit admission across two academic medical centers.

Research square·2026
Same author

Topic-Aware Summarization of Lived Health Care Experiences: Large Language Model Evaluation Study.

JMIR medical informatics·2026

相关实验视频

Updated: Jan 17, 2026

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

1.3K

在国家ENACT网络中开发和验证自然语言处理算法.

Yanshan Wang1,2,3, Jordan Hilsman1,2, Chenyu Li1,2,3

  • 1Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA.

Journal of clinical and translational science
|September 22, 2025
PubMed
概括

ENACT NLP工作组在13个地点成功部署了自然语言处理基础设施,使得人们可以访问临床叙述进行翻译研究. 这表明了联合NLP部署的可行性,并强调了解决数据异质性的重要性.

关键词:
在 ENACT 中,我们可以看到:翻译研究是翻译研究.电子健康记录是电子医疗记录.自然语言处理自然语言处理.网络 网络 网络 网络 网络 网络

更多相关视频

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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

Published on: December 6, 2024

1.0K
Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems
08:42

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

Published on: May 5, 2015

12.6K

相关实验视频

Last Updated: Jan 17, 2026

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

1.3K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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

Published on: December 6, 2024

1.0K
Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems
08:42

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

Published on: May 5, 2015

12.6K

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.
  • 翻译研究是翻译研究.

背景情况:

  • 电子健康记录 (EHR) 数据对于推进翻译研究和人工智能至关重要.
  • 电子健康记录中的临床叙述包含有价值的信息,需要自然语言处理 (NLP) 来进行研究.
  • ENACT网络的目标是通过57个临床和翻译科学奖 (CTSA) 枢纽提供对结构化EHR数据的访问.

研究的目的:

  • 建立和运营ENACT NLP工作组,使NLP衍生的临床信息在ENACT网络中可访问和查询.
  • 开发和验证NLP算法用于特定疾病背景下的各种临床任务.
  • 扩展ENACT本体学和共同数据模型,以纳入NLP衍生数据,同时确保与SHRINE等现有研究网络的兼容性.

主要方法:

  • 成立了ENACT NLP工作组,其中13个地点根据获得临床笔记,IT基础设施,NLP专业知识和机构支持而被选中.
  • 将网站组织成五个重点小组,针对特定的临床任务,每个小组包括开发和验证网站.
  • 扩展了ENACT本体学,标准化了NLP衍生数据,并使用开放健康自然语言处理 (OHNLP) 工具包进行了多站点评估.

主要成果:

  • 实现了100%的站点保留,并在所有参与站点成功部署了NLP基础设施.
  • 开发并验证了NLP算法,用于表型罕见疾病,健康的社会决定因素,阿片类药物使用障碍,睡眠和妄想.
  • 在不同地点观察到性能变化 (F1分数为0.53-0.96),强调了数据异质对NLP模型概括性的影响.

结论:

  • 在大型,联合的研究网络中展示了部署NLP基础设施的可行性.
  • 焦点小组方法被发现比通用NLP策略更实用.
  • 发现的关键挑战包括数据异质性和需要强大的协作治理,为其他网络为实现NLP用于翻译研究提供基础.