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

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

382
Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
382
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

143
Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
143
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

290
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
290

You might also read

Related Articles

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

Sort by
Same author

Characterization of IgG N-glycan patterns in COVID-19, sepsis and healthy subjects.

Scientific reports·2026
Same author

ECG-Gated 4D-CTA Assessment of Intracranial Aneurysm Wall Dynamics and Longitudinal Size Change: An Exploratory Study.

Neurology international·2026
Same author

Multivariable Serum Creatinine Forecasting for Acute Kidney Injury Detection Using an Explainable Transformer-based Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Untargeted metabolomics and proteomics reveal the versatile effects of myeloperoxidase-oxidized LDL on endothelial cells.

Biochimica et biophysica acta. General subjects·2025
Same author

Immobilization of human myeloperoxidase on silica gel for inhibitors assessment.

Journal of pharmaceutical and biomedical analysis·2025
Same author

A Model for the Formation of Beliefs and Social Norms Based on the Satisfaction Problem (SAT).

Entropy (Basel, Switzerland)·2025

Related Experiment Video

Updated: Sep 30, 2025

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

551

Personalized pathology test for Cardio-vascular disease: Approximate Bayesian computation with discriminative summary

Ritabrata Dutta1, Karim Zouaoui Boudjeltia2, Christos Kotsalos3

  • 1University of Warwick, United Kingdom.

Plos Computational Biology
|March 10, 2022
PubMed
Summary

This study introduces a new model for cardio/cerebrovascular diseases (CVD) detection, improving accuracy by analyzing platelet behavior. This personalized approach offers better diagnostics and treatment strategies for patients.

More Related Videos

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
07:51

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Published on: September 26, 2018

7.7K
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

15.8K

Related Experiment Videos

Last Updated: Sep 30, 2025

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

551
Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
07:51

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Published on: September 26, 2018

7.7K
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

15.8K

Area of Science:

  • Biomedical Engineering
  • Computational Biology
  • Cardiovascular Research

Background:

  • Cardio/cerebrovascular diseases (CVD) pose significant health challenges.
  • Current pathology tests for CVD are limited, failing to account for platelet activation dynamics and inter-individual variability.

Purpose of the Study:

  • To develop a novel stochastic platelet deposition model for enhanced CVD detection.
  • To create an inferential scheme for estimating biologically meaningful model parameters.
  • To enable personalized pathology testing and treatment for CVD.

Main Methods:

  • Developed a stochastic platelet deposition model.
  • Employed approximate Bayesian computation with a discriminating summary statistic for parameter inference.
  • Collected and analyzed data from healthy volunteers and diverse patient groups.

Main Results:

  • Successfully inferred specific biological parameters differentiating patient types.
  • Identified biological reasoning behind dysfunction in various patient cohorts.
  • Demonstrated the model's capability to capture inter-individual variability in platelet dynamics.

Conclusions:

  • The proposed model and inferential scheme offer a pathway to personalized CVD pathology tests.
  • This approach allows for a deeper understanding of the biological basis of CVD in individual patients.
  • Opens new avenues for targeted medical treatments for cardio/cerebrovascular diseases.