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

Cardiomyopathy V: Interprofessional Care01:29

Cardiomyopathy V: Interprofessional Care

22
Managing cardiomyopathy involves addressing underlying or precipitating causes, treating heart failure with medications, and implementing dietary changes and a balanced exercise and rest regimen.Lifestyle ModificationsCardiomyopathy patients should adopt a low-sodium diet to reduce fluid retention and manage heart failure. A personalized exercise and rest plan helps maintain physical fitness without overstraining the heart. Avoiding alcohol and tobacco is essential to prevent further damage to...
22
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.7K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.7K
Cardiomyopathy II: Dilated Cardiomyopathy01:30

Cardiomyopathy II: Dilated Cardiomyopathy

16
Dilated cardiomyopathy, or DCM, is a progressive myocardial disorder characterized by ventricular chamber dilation and contractile dysfunction.EtiologyVarious factors can cause DCM, including hypertension and heavy alcohol intake, which contribute to the weakening and enlargement of the heart muscle. Viral infections, such as Coxsackievirus B, adenoviruses, and influenza, can lead to DCM by causing inflammation and damage to heart tissue. Certain chemotherapeutic agents, including daunorubicin,...
16

You might also read

Related Articles

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

Sort by
Same author

Real-time prediction of atrial fibrillation in intensive care unit: a meta-learning approach.

JAMIA open·2026
Same author

Resistant Hypertension Variants Link to Hyperaldosteronism and Potassium Levels.

Hypertension (Dallas, Tex. : 1979)·2026
Same author

Artificial stupidity or logimorphism? How misuse of language warps our thinking about 'artificial intelligence'.

European heart journal. Digital health·2026
Same author

From guideline gaps to generated evidence: a blueprint for digitally integrated trials.

European heart journal·2026
Same author

The immunoproteome and multimorbidity: A Mendelian randomization study.

Science advances·2026
Same author

Big Data and Trustworthy AI for Heart Failure: A Review.

Circulation. Heart failure·2026

Related Experiment Video

Updated: Aug 12, 2025

In Silico Clinical Trials for Cardiovascular Disease
09:09

In Silico Clinical Trials for Cardiovascular Disease

Published on: May 27, 2022

1.8K

Artificial intelligence in cardiology: the debate continues.

Folkert W Asselbergs1,2,3, Alan G Fraser4,5

  • 1Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, Netherlands.

European Heart Journal. Digital Health
|January 30, 2023
PubMed
Summary

Artificial intelligence (AI) and machine learning (ML) offer advanced methods for analyzing complex medical data. However, rigorous evidence and transparent, interpretable AI are crucial for clinical adoption and improved patient outcomes.

Keywords:
Artificial intelligenceEvidence-based practiceMachine learning

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
Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

365

Related Experiment Videos

Last Updated: Aug 12, 2025

In Silico Clinical Trials for Cardiovascular Disease
09:09

In Silico Clinical Trials for Cardiovascular Disease

Published on: May 27, 2022

1.8K
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
Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

365

Area of Science:

  • Cardiovascular Medicine
  • Artificial Intelligence
  • Machine Learning

Background:

  • The rapid advancement of digital medical imaging, genomic databases, and biobanks necessitates novel analytical approaches.
  • Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into clinical practice, leading to a surge in related scientific literature.
  • Debate exists regarding the transformative potential of AI in cardiovascular medicine versus the need for caution and further evidence.

Purpose of the Study:

  • To summarize the key arguments presented in a debate on AI in cardiovascular medicine at the 2021 Congress of the European Society of Cardiology.
  • To highlight the critical need for advanced analytical techniques when conventional statistical methods are insufficient.
  • To emphasize that AI applications should prioritize hypothesis testing and clinical problem-solving over simply finding new uses for AI.

Main Methods:

  • Review and synthesis of opposing arguments presented at a major cardiology congress.
  • Discussion of the role of AI and ML as advanced analytical tools.
  • Examination of regulatory and clinical trust considerations for AI implementation.

Main Results:

  • AI and ML are powerful tools but require careful consideration, especially when conventional methods fall short.
  • Transparency and interpretability of AI/ML methods are paramount for regulatory approval and clinical decision support.
  • Few AI applications have definitively demonstrated a positive impact on clinical outcomes to date.

Conclusions:

  • AI should be viewed as an advanced analytical technique, not an end in itself; its primary goal must be to address clinical needs.
  • Physician understanding and collaboration with AI engineers are essential for effective implementation.
  • Substantial investment in research is required to validate AI's clinical utility and ensure positive patient outcomes.