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Related Concept Videos

Time-Series Graph00:54

Time-Series Graph

A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the lowest drug...
Noncompartmental Analysis: Statistical Moment Theory00:56

Noncompartmental Analysis: Statistical Moment Theory

Noncompartmental analyses leverage statistical moment theory to examine time-related changes in macroscopic events, encapsulating the collective outcomes stemming from the constituent elements in play. Statistical moment theory is a mathematical approach used to describe the time course of drug concentration in the body without assuming a specific compartmental model. SMT provides insights into drug absorption, distribution, metabolism, and elimination by treating drug concentration versus time...
Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
Time Course of Drug Effect01:14

Time Course of Drug Effect

The progression of a drug's impact can be analyzed by examining both the concentration-time course and the effect-time course. The concentration-time course is determined by the drug's half-life and is influenced by factors such as its pharmacokinetics, including absorption, distribution, metabolism, and elimination. The effect of the drug is often related to its concentration in the plasma and is calculated using the maximum drug effect and the plasma concentration that generates 50 percent of...
Increasing Function01:18

Increasing Function

An increasing function exhibits a rise in output values as input values increase. This behavior is depicted graphically as a curve or line that slopes upward from left to right. Such a function satisfies the condition that if x1 < x2, then f(x1) < f(x2), indicating that the function values grow with increasing inputs. This concept is fundamental in understanding growth trends across various domains, such as population dynamics, financial investments, or resource consumption.The average...

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Related Experiment Video

Updated: Jun 14, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

MLTrends: Graphing MEDLINE term usage over time.

Gareth A Palidwor1, Miguel A Andrade-Navarro

  • 1Ottawa Hospital Research Institute. gpalidwor@ohri.ca.

Journal of Biomedical Discovery and Collaboration
|March 25, 2010
PubMed
Summary
This summary is machine-generated.

Researchers can now easily track biomedical research trends using MLTrends, a web application that analyzes term usage in the MEDLINE database. This tool simplifies the complex task of understanding historical shifts in scientific focus.

Related Experiment Videos

Last Updated: Jun 14, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Area of Science:

  • Biomedical Informatics
  • Medical Literature Analysis
  • Bibliometrics

Background:

  • The MEDLINE database contains over 18 million records, offering a rich source for historical analysis of research trends.
  • Chronological analysis of MEDLINE records is typically complex and time-consuming for researchers and clinicians.
  • Understanding historical shifts in research areas is crucial for scientific progress.

Purpose of the Study:

  • To develop a user-friendly tool for analyzing historical trends in biomedical research.
  • To enable researchers and doctors to easily determine the emergence dates and usage intensity of biomedical terms.
  • To simplify the complex process of analyzing large-scale medical literature data.

Main Methods:

  • Development of the MLTrends web application.
  • Utilizing chronological analysis of term usage within the MEDLINE database.
  • Graphing term frequency over time to visualize trends.

Main Results:

  • MLTrends provides a straightforward method for analyzing historical changes in biomedical research.
  • The application allows for the identification of when specific biomedical terms emerged and how their usage has varied.
  • Facilitates a deeper understanding of the evolution of scientific focus within the medical field.

Conclusions:

  • MLTrends offers a valuable and accessible resource for exploring the history of biomedical research.
  • The tool democratizes the analysis of large medical literature datasets.
  • Simplifies trend analysis for researchers and clinicians, aiding in identifying emerging research areas.