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相关概念视频

Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

702
Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
702
Clinical Trials01:16

Clinical Trials

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Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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Naturalistic Observations02:30

Naturalistic Observations

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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

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The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
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Larynx01:21

Larynx

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The human larynx, often referred to as the voice box, is an intricate organ located in the neck. It serves as a pathway for air to enter the lungs during respiration and is an essential component of voice production.
Anatomy of the Larynx
The larynx consists of various components, including cartilage, muscles, and vocal cords. Its structure includes three large unpaired cartilages—the thyroid, cricoid, and epiglottis—and three smaller paired cartilages—the arytenoids,...
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Improving Translational Accuracy02:07

Improving Translational Accuracy

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相关实验视频

Updated: May 22, 2025

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

Published on: December 6, 2024

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在临床自然语言处理中使用大型语言模型进行断言检测.

Yuelyu Ji1, Zeshui Yu2, Yanshan Wang3

  • 1Dept. of Computing and Information, University of Pittsburgh, Pittsburgh, US.

Proceedings. IEEE International Conference on Healthcare Informatics
|March 17, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了大型语言模型 (LLM),用于在临床自然语言处理 (NLP) 中改进断言检测,增强医学概念理解和患者护理.

关键词:
断言检测检测 断言检测在上下文学习学习学习.大型语言模型洛拉微调精细调整

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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相关实验视频

Last Updated: May 22, 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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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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科学领域:

  • 临床自然语言处理 (NLP)
  • 医疗保健中的人工智能
  • 医疗信息学 医疗信息学

背景情况:

  • 断言检测对于理解临床笔记中的医学概念至关重要,从而影响患者的护理.
  • 传统的断言检测方法是劳动密集型的,可能会错过细微差别.
  • 准确的断言检测需要确定医疗概念的确定性,时间性和体验者.

研究的目的:

  • 开发和评估使用大型语言模型 (LLM) 检测断言的新方法.
  • 用先进的推理技术和微调来增强基于LLM的断言检测.
  • 提高在临床NLP任务中断言检测的准确性和通用性.

主要方法:

  • 在广泛的医疗数据上使用预训练的大型语言模型 (LLM).
  • 综合高级推理技术:思维树 (ToT),思维链 (CoT) 和自我一致性 (SC).
  • 应用低级调整 (LoRA) 用于模型微调.

主要成果:

  • 在i2b2 2010断言数据集上获得0.89的微平均F-1得分,这是0.11的改进.
  • 在局部睡眠概念数据集上,F-1得分为0.74的证明了概括性,0.31的改进.
  • 在临床NLP中,LLM显示了推进断言检测的巨大潜力.

结论:

  • 大型语言模型为临床NLP中断言检测提供了一种可行和有效的方法.
  • 拟议的基于LLM的方法在准确性和通用性方面明显优于以前的方法.
  • 这种方法可以与其他基于LLM的模型集成,用于全面的临床NLP解决方案.