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相关概念视频

Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
X-ray Imaging01:24

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...
Clinical Trials: Overview01:11

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
Imaging Studies VII: Vascular Imaging01:19

Imaging Studies VII: Vascular Imaging

DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...

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相关实验视频

Updated: Jun 10, 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

成像试验中的元数据质量:基于知识图的方法.

Alaa Bejaoui1, Tim Kilgus1, Heiko Tzschätzsch1

  • 1Charité - Universitätsmedizin Berlin, Institute of Medical Informatics, Germany.

Studies in health technology and informatics
|May 17, 2025
PubMed
概括

我们开发了一种方法来将DICOM元数据转换为知识图,从而实现对成像试验的先进分析和自动化质量评估. 这有助于进行可靠的数据质量检查,这对于复杂的研究研究至关重要.

关键词:
迪科姆公司 (DICOM)影像试验试验 影像试验知识图表知识图表超级数据质量 超级数据质量

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

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相关实验视频

Last Updated: Jun 10, 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

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

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

科学领域:

  • 医学成像信息学 医疗成像信息学
  • 数据科学数据科学数据科学
  • 临床试验 临床试验

背景情况:

  • 医学数字成像和通信 (DICOM) 是医学成像的标准.
  • 管理和分析DICOM元数据是复杂的,特别是在大型成像试验中.
  • 确保元数据质量对于临床试验结果的有效性至关重要.

研究的目的:

  • 介绍一种用于将DICOM元数据转化为结构化知识图的新方法.
  • 为DICOM元数据提供先进的分析能力.
  • 为了促进成像试验中的自动化元数据质量评估.

主要方法:

  • 开发一个转换管道,将DICOM元数据转换为知识图格式.
  • 实施定制指标来评估元数据质量属性,如完整性.
  • 对自动化质量控制程序的知识图的应用.

主要成果:

  • 成功地将DICOM元数据转化为可查询的知识图.
  • 使用定义的自定义指标进行元数据质量评估的演示.
  • 验证该方法在成像试验中的自动质量检查中的实用性.

结论:

  • 拟议的方法为通过知识图利用DICOM元数据提供了一个强大的框架.
  • 可以实现元数据的自动化质量评估,从而提高临床研究中的数据完整性.
  • 这种方法为管理复杂,多方面的成像试验提供了实际的好处.