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Related Concept Videos

Ischemic Heart Disease: Overview01:17

Ischemic Heart Disease: Overview

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Ischemic heart disease occurs when the heart's blood supply dwindles, causing an ominous lack of oxygen and nutrients. This deficiency, stemming from reduced or obstructed blood flow, spells danger, leading to heart muscle damage and dysfunction.
Atherosclerosis, the primary malefactor, orchestrates this dangerous condition. It manifests as the accumulation of fatty deposits, akin to insidious plaques, within arterial walls. As time elapses, these plaques metamorphose, hardening and...
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Heart Failure Drugs: Inhibitors of Renin-Angiotensin System01:26

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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...
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Related Experiment Video

Updated: May 29, 2025

Model of Ischemic Heart Disease and Video-Based Comparison of Cardiomyocyte Contraction Using hiPSC-Derived Cardiomyocytes
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Artificial Intelligence in Ischemic Heart Disease Prevention.

Shyon Parsa1, Priyansh Shah2, Ritu Doijad3

  • 1Department of Internal Medicine, Stanford University School of Medicine, Stanford, CA, USA.

Current Cardiology Reports
|February 1, 2025
PubMed
Summary

Artificial intelligence (AI) enhances ischemic heart disease (IHD) prevention through advanced risk prediction and personalized care. Addressing ethical concerns and ensuring equitable access are crucial for integrating AI into cardiology workflows.

Keywords:
Artificial intelligenceCardiovascular imagingExplainable AIFederated learningIschemic heart diseasePreventive cardiology

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Preventive Medicine

Background:

  • Ischemic heart disease (IHD) remains a leading cause of mortality worldwide.
  • Traditional risk assessment methods have limitations in precision and personalization.
  • The integration of artificial intelligence (AI) presents a paradigm shift in preventive cardiology.

Purpose of the Study:

  • To review the transformative potential of AI in preventing ischemic heart disease (IHD).
  • To explore AI advancements in predictive modeling, biomarker discovery, and cardiovascular imaging for IHD prevention.
  • To discuss considerations for the clinical integration of AI into preventive cardiology.

Main Methods:

  • Review of current literature on AI applications in cardiovascular disease prevention.
  • Analysis of AI-driven tools, including machine learning (ML) models, for risk prediction.
  • Examination of AI's role in biomarker discovery and cardiovascular imaging analysis.

Main Results:

  • AI significantly improves IHD risk prediction by integrating multimodal data, surpassing traditional methods in accuracy.
  • AI applications show promise in biomarker discovery and enhancing cardiovascular imaging interpretation.
  • Challenges include ensuring algorithm fairness, mitigating bias, and enhancing explainability for ethical deployment.

Conclusions:

  • AI holds substantial promise for reshaping preventive cardiology, enabling more precise risk assessment and personalized patient care.
  • Emerging technologies like federated learning and explainable AI are paving the way for equitable and robust AI adoption.
  • Overcoming barriers related to equity, transparency, and stakeholder engagement is vital for successful clinical integration and improved cardiovascular outcomes.