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

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 squares (OLS)...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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

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...
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...

You might also read

Related Articles

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

Sort by
Same author

Clinical drug report generation using multi-phase prompt large language models.

Scientific reports·2026
Same author

SMN deficiency contributes to osteoporosis in spinal muscular atrophy by impairing Snap23 meditated muscle-derived extracellular vesicle secretion.

Journal of translational medicine·2026
Same author

Deep Learning-Driven Transmission Electron Microscopy Analysis of Murine Optic Nerve Myelinated Axons.

Ophthalmology science·2026
Same author

Global, regional, and national burden trends of spinal fractures from 1990 to 2021: a population-based study.

International journal of surgery (London, England)·2025
Same author

Improving the Effectiveness of Adolescent Idiopathic Scoliosis (AIS) Screening: A Prospective Study.

Spine·2025
Same author

The impact of intraoperative prone lumbar fluoroscopy under anesthesia on the selection of lowest instrumented vertebra and surgical outcomes in adolescent idiopathic scoliosis with lumbar structural curves.

BMC musculoskeletal disorders·2025
Same journal

Multimodal Contrastive Spatiotemporal Self-Organizing Neural Networks for In-Home Activity Learning of Mild Cognitive Impairment.

IEEE journal of biomedical and health informatics·2026
Same journal

Integrating Multi-View Residue Graph and Protein Language Model for Cell-Penetrating Peptide Prediction via Global-Local Graph Aggregation and Cross-Attentive Fusion.

IEEE journal of biomedical and health informatics·2026
Same journal

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

IEEE journal of biomedical and health informatics·2026
Same journal

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

IEEE journal of biomedical and health informatics·2026
Same journal

stDGCN: A dual-augmentation graph convolutional network for identifying spatial domains with attention mechanism.

IEEE journal of biomedical and health informatics·2026
Same journal

Patient-specific Biomechanical Investigation of Percutaneous Pulmonary Valves: Towards the Integration of Routinely Acquired Clinical Data and Fluid-structure Interaction Simulations.

IEEE journal of biomedical and health informatics·2026
See all related articles

Related Experiment Videos

Knowledge-assisted sequential pattern analysis with heuristic parameter tuning for labor contraction prediction.

Zifang Huang, Mei-Ling Shyu, James M Tien

    IEEE Journal of Biomedical and Health Informatics
    |September 24, 2013
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel method using AI to predict labor contractions, enabling optimal remifentanil dosing for labor pain relief. The approach ensures maximum pain relief during contractions with minimal effects between them.

    Related Experiment Videos

    Area of Science:

    • Anesthesiology
    • Artificial Intelligence
    • Biomedical Engineering

    Background:

    • Effective labor pain management requires precise timing of analgesics like remifentanil.
    • Current methods may not optimally balance efficacy during contractions with minimal effect between them.

    Purpose of the Study:

    • To develop an AI-driven system for predicting intrauterine pressure changes to time remifentanil administration.
    • To optimize remifentanil dosing for labor pain relief, maximizing efficacy during contractions.

    Main Methods:

    • Knowledge-assisted sequential pattern analysis with heuristic parameter tuning.
    • Sequential association rule mining for patient data selection.
    • Least squares support vector machine (RBF kernel) for time series prediction.

    Main Results:

    • The proposed framework demonstrated significantly lower prediction errors compared to existing methods.
    • The system accurately predicts intrauterine pressure changes indicating contractions.
    • Heuristic parameter tuning adapted to time series characteristics.

    Conclusions:

    • The developed AI framework offers a promising approach for precise remifentanil dosing during labor.
    • This method can enhance labor pain management by optimizing drug efficacy and minimizing side effects.