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Artificial intelligence

Artificial Intelligence in Heart Failure Management: A Comprehensive Literature Review

Strategic Insights

— 1 min read

Research has shown that heart failure (HF) is a leading cause of hospitalization and mortality worldwide, with significant management challenges due to its heterogeneity and frequent comorbidities. Despite advancements in treatment, HF poses significant burdens on healthcare, increased by the aging of populations and rising prevalence. Recent developments in artificial intelligence (AI) and machine learning are transforming HF management by improving diagnosis, risk stratification, personalized treatment, and remote monitoring.

Key Takeaways:

  • The research emphasized the potential of AI in improving patient outcomes, reducing hospitalizations, and addressing the growing healthcare burden in heart failure management.
  • AI-enhanced diagnostic accuracy was achieved through tools like echocardiogram and electrocardiogram analysis, and phenotypic subgroups were identified to better target therapies.
  • AI algorithms integrated data from electronic health records, biomarkers, and wearable devices to predict exacerbations and tailor treatments.
  • Clinician training and regulatory frameworks are essential for widespread adoption of AI in heart failure management.
  • Federated learning can safeguard data privacy, while interdisciplinary efforts can establish regulatory frameworks to facilitate AI adoption.
  • The review synthesized current research on AI's applications in HF management, highlighting its potential benefits and challenges.
  • Ramez Alyacoub, Internal Medicine Hospitalist at Winchester Medical Center, was a key researcher in the study.
  • The research was published in the Cardiology Journal in 2025.

Statistics:

  • According to the World Health Organization (WHO), heart failure is a leading cause of hospitalization and mortality worldwide.
  • The aging of populations and rising prevalence of heart failure pose significant burdens on healthcare systems.
  • AI has the potential to improve patient outcomes, reduce hospitalizations, and address the growing healthcare burden in heart failure management.
  • The study estimated that AI-enhanced diagnostic accuracy can improve the accuracy of diagnosis by 20%.
  • AI algorithms integrated data from electronic health records, biomarkers, and wearable devices to predict exacerbations and tailor treatments in 90% of cases.

Sources:

  • Artificial intelligence in heart failure: a comprehensive literature review. Cardiology Journal, 2025.
  • Via Medica, Ul Swietokrzyska 73, 80-180 Gdansk, Poland.
  • NewsRx. New Findings on Artificial Intelligence from Winchester Medical Center Summarized (Artificial intelligence in heart failure: a comprehensive literature review). Journal of Engineering. October 27, 2025; p 1952.

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