Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

X-ray Crystallography02:18

X-ray Crystallography

26.6K
The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...
26.6K
X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

5.1K
X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are  scattered by the electron clouds around the sample atoms. The  X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal...
5.1K
X-ray Imaging01:24

X-ray Imaging

10.9K
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...
10.9K
Determination of Crystal Structures01:29

Determination of Crystal Structures

32
In the late 1800s, the revelation that light extended beyond visible wavelengths led to the discovery of X-rays by Wilhelm Roentgen. Recognized as high-energy electromagnetic radiation with short wavelengths, X-rays prompted exploration into their interaction with crystals. Max von Laue proposed in 1912 that the periodic arrangement of atoms, ions, or molecules in crystals would cause them to diffract X-rays, a hypothesis confirmed through experiments with copper sulfate and zinc sulfide...
32
Scanning Electron Microscopy01:07

Scanning Electron Microscopy

5.8K
A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
Fundamental Principles
Accelerated...
5.8K
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

564
The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...
564

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cell2Grid: an efficient, spatial, and convolutional neural network-ready representation of cell segmentation data.

Journal of medical imaging (Bellingham, Wash.)·2022
Same author

Pheromone communication among sexes of the garden cross spider Araneus diadematus.

Die Naturwissenschaften·2021
Same author

Sequence Ontology terminology for gene regulation.

Biochimica et biophysica acta. Gene regulatory mechanisms·2021
Same author

On beyond Gruber: "Ontologies" in today's biomedical information systems and the limits of OWL.

Journal of biomedical informatics·2021
Same author

SR-17018 Stimulates Atypical µ-Opioid Receptor Phosphorylation and Dephosphorylation.

Molecules (Basel, Switzerland)·2021
Same author

Ethik in der Medizin : Organ der Akademie fur Ethik in der Medizin·2021
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Mar 12, 2026

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
10:12

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples

Published on: June 19, 2018

9.7K

Structural Patterns under X-Rays: Is SNOMED CT Growing Straight?

Pablo López-García1, Stefan Schulz1

  • 1Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.

Plos One
|November 5, 2016
PubMed
Summary
This summary is machine-generated.

Analyzing structural patterns in SNOMED CT revealed modeling issues. Most patterns were concentrated in specific areas, with low reuse, indicating potential problems in the electronic health record ontology.

More Related Videos

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering
07:19

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Published on: November 5, 2018

13.5K
Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

1.7K

Related Experiment Videos

Last Updated: Mar 12, 2026

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
10:12

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples

Published on: June 19, 2018

9.7K
Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering
07:19

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Published on: November 5, 2018

13.5K
Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

1.7K

Area of Science:

  • Medical Informatics
  • Ontology Engineering
  • Health Data Modeling

Background:

  • Large-domain ontologies like SNOMED CT are crucial for electronic health records.
  • Unprincipled modeling decisions can hinder ontology quality and usability.
  • Previous methods for identifying issues focused on concept clustering, not root causes.

Purpose of the Study:

  • To investigate the structural patterns within the SNOMED CT data model.
  • To understand how these patterns reflect editors' modeling strategies.
  • To identify problematic modeling decisions and their origins.

Main Methods:

  • Examination of underlying structural patterns in the SNOMED CT data model.
  • Analysis of pattern distribution across SNOMED CT sub-hierarchies.
  • Qualitative analysis of low-reuse (singleton) patterns.

Main Results:

  • 92% of structural patterns were concentrated in the Procedure and Clinical finding sub-hierarchies.
  • Pattern reuse was low, with over 30% of patterns used only once.
  • Qualitative analysis of singleton patterns revealed issues like redundancy, omission, and inconsistency.

Conclusions:

  • Analysis of structural patterns is a valuable technique for identifying problematic areas in SNOMED CT.
  • Observed patterns offer insights into the modeling styles of SNOMED CT editors.
  • Identifying common patterns can inform template creation and refinement for SNOMED CT.