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Related Concept Videos

Classification of Systems-I01:26

Classification of Systems-I

Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Classification of Systems-II01:31

Classification of Systems-II

Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
State Space Representation01:27

State Space Representation

The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Structural Classification of Joints01:20

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
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Stereotype Content Model02:16

Stereotype Content Model

The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence categorization, a person will feel...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

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Related Experiment Videos

Rule-based support system for multiple UMLS semantic type assignments.

James Geller1, Zhe He, Yehoshua Perl

  • 1New Jersey Institute of Technology, Newark, NJ 07102-1982, United States.

Journal of Biomedical Informatics
|October 9, 2012
PubMed
Summary
This summary is machine-generated.

A new computational system, adviseEditor, helps Unified Medical Language System (UMLS) editors identify permissible semantic type combinations. This tool aims to reduce errors and accelerate the assignment of semantic types to new concepts.

Related Experiment Videos

Area of Science:

  • Medical Informatics
  • Computational Linguistics
  • Knowledge Representation

Background:

  • The Unified Medical Language System (UMLS) assigns semantic types to concepts, but not all combinations are permissible.
  • Errors in semantic type assignment for rare combinations are common and costly to correct.
  • UMLS editors require tools to validate semantic type assignments.

Purpose of the Study:

  • To design a computational system to assist UMLS editors in determining the permissibility of semantic type combinations.
  • To validate combinations of two, three, four, or five semantic types.
  • To flag prohibited or questionable semantic type assignments.

Main Methods:

  • Identified inclusion/exclusion rules from UMLS Semantic Network documentation.
  • Derived rule-categories from UMLS concept content.
  • Developed the adviseEditor algorithm and a web-based system to implement it.

Main Results:

  • Eight distinct rule-categories were identified.
  • The adviseEditor system successfully classifies semantic type combinations as permitted, prohibited, or questionable.
  • Analysis of semantic type pairs across rule-categories and illustration of rule-contradicting cases were performed.

Conclusions:

  • The adviseEditor system effectively integrates explicit and implicit UMLS knowledge.
  • It provides guidance to UMLS editors on semantic type combination permissibility.
  • This tool has the potential to expedite editor workflow and minimize erroneous semantic type assignments.