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Related Concept Videos

Methods of Documentation I: Source-Oriented Records01:18

Methods of Documentation I: Source-Oriented Records

Source-oriented records, or SOR, are medical record-keeping organized by the data source. The SOR system was first developed in the mid-1900s to organize the growing patient data in hospitals and other healthcare facilities.
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Nursing Clinical Information System01:27

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Network Function of a Circuit01:25

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Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
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SBAR I: Understanding the Concept

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SN2 Reaction: Stereochemistry02:23

SN2 Reaction: Stereochemistry

In an SN2 reaction, the nucleophilic attack on the substrate and departure of the leaving group occurs simultaneously through a transition state. As the nucleophile approaches the substrate from the back-side, the configuration of the substrate carbon changes from tetrahedral to trigonal bipyramidal and then back to tetrahedral, leading to an inversion in the configuration of the product.
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Assembly of Signaling Complexes01:30

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Related Experiment Video

Updated: Jun 14, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

Auditing SNOMED relationships using a converse abstraction network.

Duo Wei1, Michael Halper, Gai Elhanan

  • 1NJIT, Newark, NJ, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|March 31, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces the converse abstraction network (CAN) to analyze SNOMED CT relationships. The CAN helps identify areas for improvement within the SNOMED CT terminology, particularly for device and procedure hierarchies.

Related Experiment Videos

Last Updated: Jun 14, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

Area of Science:

  • Medical Informatics
  • Ontology Engineering
  • Knowledge Representation

Background:

  • SNOMED CT defines attribute relationships between source and target hierarchies.
  • Some hierarchies lack outgoing relationships, limiting their structural representation.
  • Converse relationships, though not explicit, offer alternative views of hierarchy structures.

Purpose of the Study:

  • To present a novel method for analyzing SNOMED CT hierarchy relationships.
  • To introduce the converse abstraction network (CAN) for deriving alternative views.
  • To develop an auditing methodology based on the CAN for SNOMED CT refinement.

Main Methods:

  • Automatic derivation of a converse abstraction network (CAN) from SNOMED CT hierarchies.
  • Formulation of an auditing methodology utilizing the CAN.
  • Application of the methodology to SNOMED CT's Device subhierarchy and Procedure hierarchy relationships.

Main Results:

  • The converse abstraction network (CAN) was successfully derived from SNOMED CT data.
  • The auditing methodology effectively identified potential areas for SNOMED CT improvement.
  • Analysis of the Device and Procedure hierarchies revealed specific refinement opportunities.

Conclusions:

  • The converse abstraction network (CAN) is a valuable tool for understanding SNOMED CT relationship structures.
  • The CAN-based auditing methodology aids in refining and improving the SNOMED CT terminology.
  • This approach offers a systematic way to enhance the completeness and accuracy of SNOMED CT.