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

253
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.
253

You might also read

Related Articles

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

Sort by
Same author

Preferences for HIV testing among partners of transgender women in Lima, Peru: a discrete choice experiment.

Journal of acquired immune deficiency syndromes (1999)·2026
Same author

Assessing VirScan serosurvey epitope profiling variability between in-clinic venous blood draw and capillary blood self-sampling device.

Microbiology spectrum·2026
Same author

Influence of B cell-lineage targeted CAR-T cell therapy on humoral immunity and vaccine-induced antibody response.

Nature communications·2026
Same author

Cytomegalovirus DNAemia in Hospitalized Adults With SARS-CoV-2 Infection Requiring Supplemental Oxygen: Virologic and Clinical Characteristics and Association With Outcomes.

The Journal of infectious diseases·2026
Same author

Sexual behaviors and access to HIV services during the COVID-19 pandemic among cisgender men who have sex with men in Lima, Peru.

BMC public health·2025
Same author

CD4-mimetics sensitize HIV-infected cells to ADCC mediated by plasma from persons with early-stage HIV-1 infection.

Journal of virology·2025

Related Experiment Video

Updated: Dec 9, 2025

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

7.9K

Selecting Biomarkers for building optimal treatment selection rules using Kernel Machines.

Sayan Dasgupta1, Ying Huang1

  • 1Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA.

Journal of the Royal Statistical Society. Series C, Applied Statistics
|September 14, 2020
PubMed
Summary

Selecting optimal biomarkers for treatment requires balancing disease burden and costs. This study introduces a method to incorporate biomarker costs into optimization, improving treatment selection rules for better patient outcomes.

Keywords:
Biomarker costFeature selectionL0 penalizationTreatment selectionWeighted support vector machines

More Related Videos

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

1.1K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.0K

Related Experiment Videos

Last Updated: Dec 9, 2025

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

7.9K
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

1.1K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.0K

Area of Science:

  • Biostatistics
  • Medical Informatics
  • Computational Biology

Background:

  • Biomarker combinations are crucial for effective treatment selection.
  • Including numerous biomarkers can increase costs and reduce model accuracy.
  • Minimizing population burden is key for optimal treatment strategies.

Purpose of the Study:

  • To develop a method for selecting optimal biomarker combinations for treatment selection.
  • To incorporate biomarker costs into the optimization process.
  • To improve the performance and cost-effectiveness of treatment-selection models.

Main Methods:

  • Formulated feature selection in optimization as minimizing an extended total burden.
  • Incorporated biomarker costs into the objective function.
  • Utilized 0-norm penalized weighted-classification for estimating linear and nonlinear combinations.

Main Results:

  • Demonstrated the importance of feature selection in biomarker combination optimization.
  • Showcased the impact of incorporating marker costs on deriving treatment-selection rules.
  • Validated the proposed methods through simulations and a real data example.

Conclusions:

  • Feature selection and marker cost integration are vital for deriving effective treatment-selection rules.
  • The proposed approach offers a more cost-efficient and accurate method for biomarker selection.
  • This methodology can lead to improved patient management and resource allocation in healthcare.