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

Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

424
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
424
Anticoagulant Drugs: Vitamin K Antagonists and Direct Oral Anticoagulants01:18

Anticoagulant Drugs: Vitamin K Antagonists and Direct Oral Anticoagulants

2.6K
Oral anticoagulants are vital tools in preventing and treating blood clotting disorders. This diverse class of medications can be categorized as vitamin K antagonists, exemplified by warfarin, and direct thrombin inhibitors (DTIs), such as dabigatran, as well as factor Xa inhibitors, including rivaroxaban.
Warfarin, a prominent vitamin K antagonist family member, exerts its effect by inhibiting the enzyme VKORC1 (vitamin K epoxide reductase complex 1). By hindering this enzyme, warfarin...
2.6K
Anticoagulant Drugs: Low-Molecular-Weight Heparins01:30

Anticoagulant Drugs: Low-Molecular-Weight Heparins

2.1K
Hemostasis is a crucial process that prevents excessive blood loss from damaged blood vessels. It involves various mechanisms such as vasoconstriction, platelet adhesion and activation, and fibrin formation. The importance of each mechanism depends on the type of vessel injury. In contrast, thrombosis is the abnormal formation of a blood clot within the blood vessels, leading to potential complications if the clot obstructs blood flow. Thrombosis can be caused by increased coagulability of the...
2.1K
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses01:25

Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

297
A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...
297
Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations01:15

Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations

300
Gentamicin, an aminoglycoside antibiotic, is commonly administered via intermittent intravenous infusion to treat severe infections. An intermittent one-hour infusion of gentamicin, administered at eight-hour intervals, allows for precise control of plasma drug concentrations, minimizing toxicity while ensuring therapeutic efficacy. Pharmacokinetic principles govern the dynamics of plasma concentrations and can be mathematically described using specific equations.The plasma drug concentration...
300
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

57
Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
57

You might also read

Related Articles

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

Sort by
Same author

Prediction of brain metastasis development with DNA methylation signatures.

Nature medicine·2024
Same author

Klotho as an Early Marker of Acute Kidney Injury Following Cardiac Surgery: A Systematic Review.

Journal of cardiovascular development and disease·2024
Same author

Optimization of chemical conditions for metabolites production by <i>Ganoderma lucidum</i> using response surface methodology and investigation of antimicrobial as well as anticancer activities.

Frontiers in microbiology·2024
Same author

Advancing Preoperative Strategies for Thyroidectomy in Graves' Disease: A Narrative Review.

Cureus·2023
Same author

Machine learning models can predict subsequent publication of North American Spine Society (NASS) annual general meeting abstracts.

PloS one·2023
Same author

The effect of Tai Chi on quality of life in male older people: A randomized controlled clinical trial.

Complementary therapies in clinical practice·2018

Related Experiment Video

Updated: Feb 27, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.1K

Multi-objective feature selection for warfarin dose prediction.

Mohammad Karim Sohrabi1, Alireza Tajik1

  • 1Department of Computer Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran.

Computational Biology and Chemistry
|July 10, 2017
PubMed
Summary

This study introduces a novel multi-objective feature selection approach for warfarin dose prediction, enhancing decision support systems in medicine. Multi-objective particle swarm optimization demonstrated superior precision for accurate anticoagulant dosing.

Keywords:
Artificial neural networksFeature selectionMulti-objective optimizationWarfarin

More Related Videos

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.9K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

1.4K

Related Experiment Videos

Last Updated: Feb 27, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.1K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.9K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

1.4K

Area of Science:

  • Pharmacogenomics
  • Medical Informatics
  • Computational Biology

Background:

  • Decision support systems are increasingly vital in medical science, particularly for drug dose prediction.
  • Warfarin, a critical anticoagulant, requires precise dosing to prevent clot formation and manage patient safety.
  • Accurate warfarin dose prediction is challenging due to individual variations influenced by clinical and genetic factors.

Purpose of the Study:

  • To propose and evaluate a novel multi-objective feature selection approach for improving warfarin dose prediction.
  • To compare the efficacy of multi-objective optimization methods against traditional feature selection techniques.
  • To assess the performance of artificial neural networks in conjunction with these advanced feature selection methods.

Main Methods:

  • Utilized a dataset of 553 patients undergoing warfarin therapy (2013-2015) with INR in the target range.
  • Extracted and evaluated clinical and genetic characteristics influencing warfarin dose.
  • Applied multi-objective optimization algorithms: Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO).
  • Evaluated artificial neural networks for dose prediction using selected features.

Main Results:

  • Multi-objective optimization methods significantly outperformed classic feature selection techniques in accuracy and performance.
  • The Multi-Objective Particle Swarm Optimization (MOPSO) algorithm exhibited higher precision compared to NSGA-II.
  • With seven selected features, MOPSO achieved a Mean Square Error (MSE) of 0.011, Root Mean Square Error (RMSE) of 0.1, and Mean Absolute Error (MAE) of 0.109.

Conclusions:

  • The proposed multi-objective feature selection approach, particularly MOPSO, offers a more accurate and precise method for warfarin dose prediction.
  • This approach enhances the capabilities of decision support systems in personalized medicine.
  • The findings suggest a pathway for improved patient outcomes through optimized anticoagulant therapy.