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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

23.1K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

250
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
250
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

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Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
534
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

244
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
244
What is a Frequency Distribution00:51

What is a Frequency Distribution

26.2K
A frequency is the number of times a value of the data occurs. The sum of all the frequency values represents the total number of students included in the sample. It is commonly used to group data of quantitative types. Frequency distributions can be displayed in a table, histogram, line graph, dot plot, or pie chart, just to name a few. A histogram is a graphical representation of tabulated frequencies, shown as adjacent rectangles, erected over discrete intervals (bins), with an area equal to...
26.2K
Mean From a Frequency Distribution01:11

Mean From a Frequency Distribution

21.5K
Sometimes, data gathered from an experiment on a large sample or population are organized into concise tables. In such cases, the frequency of the quantitative data set is plotted in the form of a table. Or else, the data values are grouped into the quantity’s intervals, which form classes, and their respective frequencies are known. That is, the data values are distributed over different categories or classes. This is known as frequency distribution.
When such a data set is encountered,...
21.5K

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Related Experiment Video

Updated: Jan 20, 2026

Designing a Bioreactor to Improve Data Acquisition and Model Throughput of Engineered Cardiac Tissues
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Improving mortality models in the ICU with high-frequency data.

James Todd1, Adrian Gepp1, Brent Richards2

  • 1Bond Business School, Bond University, Gold Coast, Queensland, Australia.

International Journal of Medical Informatics
|August 25, 2019
PubMed
Summary
This summary is machine-generated.

Intensive Care Unit (ICU) scoring systems can be enhanced using high-frequency data. Analyzing turning points in patient

Keywords:
APACHEAcute physiology and chronic health evaluation IIIHigh frequency dataIntensive careMortality predictionSeverity scores

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Objective Nociceptive Assessment in Ventilated ICU Patients: A Feasibility Study Using Pupillometry and the Nociceptive Flexion Reflex
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Area of Science:

  • Critical Care Medicine
  • Health Informatics
  • Biostatistics

Background:

  • Effective Intensive Care Unit (ICU) performance assessment is crucial for optimal healthcare resource allocation.
  • Current ICU severity scoring systems are continuously researched for improvements using advanced techniques and novel variables.
  • High-frequency data from automated monitoring systems offer potential for enhancing patient assessment.

Purpose of the Study:

  • To investigate the improvement of ICU scoring systems through the utilization of high-frequency data metrics.
  • To evaluate whether summarizing high-frequency physiological data can enhance the predictive performance of existing scoring systems.

Main Methods:

  • Utilized data from 3128 admissions to Gold Coast University Hospital ICU.
  • Constructed three logistic regression models based on the APACHE III scoring system.
  • Compared models with and without high-frequency data predictors (pulse, mean arterial pressure) against a baseline model.
  • Assessed model performance using accuracy, calibration, and discrimination metrics.

Main Results:

  • Models incorporating high-frequency predictors demonstrated improved discrimination and accuracy.
  • Calibration remained consistent across all models.
  • The number of turning points in mean arterial pressure or pulse within the first 24 hours significantly influenced model performance.

Conclusions:

  • ICU scoring systems can be significantly improved by incorporating high-frequency data summaries.
  • The analysis of physiological signal dynamics, such as turning points, offers a valuable approach for enhancing patient severity assessment.