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 Experiment Videos

Fitting linear compartmental models by a matrix diagonalization method.

C D Russell1

  • 1University of Alabama Hospital and VA Medical Center, Birmingham, AL 35233, USA. crussell@uabmc.edu

Nuclear Medicine Communications
|July 27, 2001
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Defining resistance and tolerance traits in Covid-19: towards a stratified medicine approach.

QJM : monthly journal of the Association of Physicians·2022
Same author

Challenges in the diagnosis of leptospirosis outwith endemic settings: a Scottish single centre experience.

The journal of the Royal College of Physicians of Edinburgh·2018
Same author

Enhanced surveillance of Staphylococcus aureus bacteraemia to identify targets for infection prevention.

The Journal of hospital infection·2016
Same author

Diagnosis and features of hospital-acquired pneumonia: a retrospective cohort study.

The Journal of hospital infection·2016
Same author

Healthcare workers' decision-making about transmission-based infection control precautions is improved by a guidance summary card.

The Journal of hospital infection·2015
Same author

Development of two real-time multiplex PCR assays for the detection and quantification of eight key bacterial pathogens in lower respiratory tract infections.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases·2015
Same journal

Diagnostic performance and quantitative characterization of PET/computed tomography in peritoneal deposits assessment.

Nuclear medicine communications·2026
Same journal

Diagnostic value of dual-time-point 18F-fluorodeoxyglucose PET/computed tomography in differentiating benign and malignant extrahepatic bile duct occupying lesions.

Nuclear medicine communications·2026
Same journal

Prognostic value of baseline 18F- fluroodexoygloucose PET/computed tomography-derived maximum standardized uptake value and tumor bulk in pediatric Hodgkin lymphoma: a retrospective analysis.

Nuclear medicine communications·2026
Same journal

A comparative assessment of [99mTc] HYNIC-PSMA-11 scintigraphy in prostate cancer as a potential substitute for disease evaluation with [68Ga] PSMA-11 PET/CT imaging.

Nuclear medicine communications·2026
Same journal

Prediction of tumor radiation absorbed dose in radionuclide therapy based on the mean standardized uptake value from PET imaging.

Nuclear medicine communications·2026
Same journal

Serum cytokine profiles in papillary thyroid carcinoma patients with lung metastases: characteristics and the relationship with prognosis.

Nuclear medicine communications·2026
See all related articles

A new, general method allows fitting experimental data to linear compartmental models using public domain software. This approach simplifies analysis for various models, including complex four-compartment systems.

Area of Science:

  • Pharmacokinetics and Pharmacodynamics
  • Systems Biology
  • Mathematical Modeling

Background:

  • Compartmental models are crucial for understanding drug disposition and biological processes.
  • Existing methods for fitting these models can be complex and software-specific.
  • A need exists for a versatile and accessible fitting method.

Purpose of the Study:

  • To present a general method for fitting experimental data to arbitrary linear compartmental models.
  • To demonstrate the method's flexibility across different compartmental model structures.
  • To provide a user-friendly approach utilizing public domain software.

Main Methods:

  • Development of a general fitting algorithm applicable to various linear compartmental models.
  • Input-driven model definition, allowing the same program to handle diverse model structures.

Related Experiment Videos

  • Utilizing readily available public domain software for accessibility and reproducibility.

    • Main Results:

    • Successful fitting of experimental data to linear compartmental models was achieved.
    • The method demonstrated adaptability to different model complexities, including a four-compartment system.
    • The approach proved effective and efficient for compartmental model analysis.

    Conclusions:

    • The presented general method offers a flexible and accessible tool for analyzing linear compartmental models.
    • This approach simplifies the process of fitting experimental data, enhancing research efficiency.
    • The method is broadly applicable across various scientific disciplines employing compartmental modeling.