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

Pathophysiology of Heart Failure01:17

Pathophysiology of Heart Failure

1.5K
Heart failure (HF) is a progressive syndrome involving ventricles that leads to inadequate cardiac output. It can be classified based on location and output or ejection fraction. Ejection fraction (EF) is an essential measurement in the diagnosis and surveillance of HF. Reduced EF corresponds to systolic heart failure (HFrEF). However, HF with preserved ejection fraction (HFpEF) is becoming increasingly prevalent. Also known as diastolic HF, this form of HF is related to aging. The...
1.5K
Heart Failure Drugs: Inhibitors of Renin-Angiotensin System01:26

Heart Failure Drugs: Inhibitors of Renin-Angiotensin System

404
The activation of the sympathetic nervous system and the renin-angiotensin-aldosterone system (RAAS) contributes to cardiac remodeling, and inhibiting the RAAS is a pharmacological target in heart failure management. As a result, neurohumoral modulation is a crucial treatment principle for managing heart failure. This approach involves using medications like ACE inhibitors (ACEIs), angiotensin receptor blockers (ARBs), β-blockers, mineralocorticoid receptor antagonists (MRAs), and neutral...
404
Imbalances in Cardiac Output01:26

Imbalances in Cardiac Output

1.4K
The heart's primary function is to pump blood throughout the body, maintaining a balance between blood sent out (cardiac output) and blood returning (venous return). If this balance is disrupted, it can result in congestive heart failure (CHF), a severe condition where the heart becomes an inefficient pump, leading to inadequate blood circulation.
CHF can occur due to the failure of either side of the heart. Left-side failure leads to pulmonary congestion—the right side continues to send...
1.4K
Heart Failure Drugs: Diuretics01:22

Heart Failure Drugs: Diuretics

352
Heart failure and kidney perfusion are interconnected in a complex way. Reduced renal perfusion and venous congestion are two significant factors that contribute to renal dysfunction in heart failure. The kidneys, primarily responsible for fluid balance in the body, are adversely affected due to compromised cardiac output and increased venous pressure. In response to reduced renal perfusion, the kidneys activate neurohumoral mechanisms to restore balance. However, these mechanisms can be...
352
Human Genetics01:28

Human Genetics

549
Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
549
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

13.2K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
13.2K

You might also read

Related Articles

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

Sort by
Same author

The LAV-BPIFB4-Platelet-CD47 Axis: A Novel Mechanism Associated With Immune Resilience in Longevity.

Aging cell·2026
Same author

Wearable technologies in neurorehabilitation and cardiac rehabilitation: A narrative review.

Journal of bodywork and movement therapies·2026
Same author

Unburdening healthcare systems through telenursing in chronic respiratory disease management: a systematic review.

Frontiers in digital health·2026
Same author

Cardiac remodeling after bariatric surgery associates with systemic metabolic reprogramming: a longitudinal untargeted metabolomics study.

Cardiovascular diabetology·2026
Same author

Perception and reality: assessing the accuracy of self-assessed dysphonia and dysphagia risk in people with cardiovascular disease.

Postgraduate medicine·2026
Same author

Are emotions measurable? A narrative review on wearable technologies between neuroscience and cardiology.

Expert review of medical devices·2026

Related Experiment Video

Updated: Jun 14, 2025

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

6.4K

An explainable model for predicting Worsening Heart Failure based on genetic programming.

Valeria Visco1, Antonio Robustelli2, Francesco Loria1

  • 1Department of Medicine, Surgery and Dentistry, University of Salerno, Via S. Allende, Baronissi (SA), 84081, Italy.

Computers in Biology and Medicine
|September 7, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new AI model for early detection of Worsening Heart Failure (WHF). The model uses Genetic Programming to predict WHF, offering interpretable results to aid clinical decisions and reduce hospitalizations.

Keywords:
Artificial IntelligenceExplainable classificationExplainable diagnosisGenetic programmingHeart failureWorsening Heart Failure

More Related Videos

A Surgical Model of Heart Failure with Preserved Ejection Fraction in Tibetan Minipigs
07:09

A Surgical Model of Heart Failure with Preserved Ejection Fraction in Tibetan Minipigs

Published on: February 18, 2022

1.8K
Implantation of an Isoproterenol Mini-Pump to Induce Heart Failure in Mice
05:08

Implantation of an Isoproterenol Mini-Pump to Induce Heart Failure in Mice

Published on: October 3, 2019

11.1K

Related Experiment Videos

Last Updated: Jun 14, 2025

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

6.4K
A Surgical Model of Heart Failure with Preserved Ejection Fraction in Tibetan Minipigs
07:09

A Surgical Model of Heart Failure with Preserved Ejection Fraction in Tibetan Minipigs

Published on: February 18, 2022

1.8K
Implantation of an Isoproterenol Mini-Pump to Induce Heart Failure in Mice
05:08

Implantation of an Isoproterenol Mini-Pump to Induce Heart Failure in Mice

Published on: October 3, 2019

11.1K

Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Heart Failure (HF) presents a significant healthcare burden, with early detection of Worsening Heart Failure (WHF) being crucial for improved patient outcomes.
  • Current AI models for cardiovascular diseases often lack transparency, leading to physician reluctance due to their 'black box' nature.

Purpose of the Study:

  • To develop a novel, interpretable diagnostic model for predicting WHF.
  • To provide a tool that assists clinicians in identifying high-risk patients for timely intervention.

Main Methods:

  • A threshold-based binary classifier was developed using a mathematical model derived from Genetic Programming (GP).
  • The model identifies key predictors of WHF, including creatinine, sPAP, and CAD, and offers a 3D graphical representation for enhanced understanding.
  • Retrospective data from 519 HF patients were analyzed.

Main Results:

  • The GP-based classifier achieved an average score of 96% across all evaluation metrics.
  • The model demonstrated superior performance compared to commonly used machine learning algorithms.
  • The interpretable nature of the model facilitated clinical staff's understanding and decision-making.

Conclusions:

  • The developed GP model effectively predicts WHF with high accuracy and interpretability.
  • This approach has the potential to significantly impact HF management by enabling earlier diagnosis, targeted treatment, and reduced hospitalizations.