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

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

244
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
244
Clearance Models: Noncompartmental Models01:17

Clearance Models: Noncompartmental Models

240
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
240
Prediction Intervals01:03

Prediction Intervals

3.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
3.3K
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

497
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
497
Aggregates Classification01:29

Aggregates Classification

964
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
964
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.1K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Implications of Liver Failure Cutoffs for Mortality Prediction in Hospitalized Cirrhosis Patients: A Multicentric Study.

Gastro hep advances·2026
Same author

Overlap Syndromes and Associated Immunoglobulin-G4-Related Liver Diseases.

Journal of clinical and experimental hepatology·2026
Same author

Recompensation and Further Decompensation After Index Decompensation in Patients with Autoimmune Hepatitis: A Real-World Study.

Digestive diseases and sciences·2026
Same author

Shifting epidemiology and disease severity: Rethinking India's hepatitis A strategy in the context of acute liver failure.

Journal of family medicine and primary care·2026
Same author

Validation of a Low-Cost Handheld Dynamometer Against a Standard Device for Handgrip Strength Assessment in Stable Outpatients with Cirrhosis.

Journal of frailty, sarcopenia and falls·2026
Same author

Proportions, trends, and outcomes of posterior circulation ischemic stroke in the United States.

Frontiers in neurology·2026
Same journal

Genetic and Genomic Insights Across the SLD Spectrum.

Clinical and molecular hepatology·2026
Same journal

Comparison of Clinical Practice Guidelines for Chronic Hepatitis B: Natural History Classification and Treatment Initiation.

Clinical and molecular hepatology·2026
Same journal

Clinical utility of liquid biopsy in biliary tract cancer: Diagnosis to treatment monitoring.

Clinical and molecular hepatology·2026
Same journal

Transitions from Combustible to Noncombustible Tobacco Use and Liver Outcomes in Steatotic Liver Disease.

Clinical and molecular hepatology·2026
Same journal

Chronic Viral Hepatitis with Concurrent MASLD: Dual Etiology Challenges.

Clinical and molecular hepatology·2026
Same journal

NAT10 deficiency in aging drives impaired liver regeneration by disrupting PARP10 in an ac4C-dependent manner.

Clinical and molecular hepatology·2026
See all related articles

Related Experiment Video

Updated: Jan 14, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.3K

Harmonized ACLF Prognostication with Explainable Machine Learning Models: Traversing from Counts to Composition

Sagnik Biswas1, Akash Roy2

  • 1Department of Gastroenterology and Human Nutrition Unit, All India Institute of Medical Sciences, New Delhi, India.

Clinical and Molecular Hepatology
|October 20, 2025
PubMed
Summary

No abstract available in PubMed .

More Related Videos

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

428

Related Experiment Videos

Last Updated: Jan 14, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.3K
Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

428