Introduction: Chronic heart failure (CHF) represents a major global health burden. This review explores the potential of artificial intelligence (AI) in improving its diagnosis, treatment, and management.
Methods: This study conducted a comprehensive literature review to evaluate the current and emerging applications of AI in CHF. Databases, such as PubMed, Scopus, and IEEE Xplore, were searched for peer-reviewed articles published between 2015 and 2025, focusing on AIbased diagnostic tools, predictive modeling, treatment personalization, and remote monitoring systems.
Results: Significant advancements were identified in AI-enhanced diagnostics, predictive models for hospital readmissions, personalized treatment optimization, and AI-driven remote monitoring systems. These technologies have demonstrated improvements in diagnostic accuracy, risk stratification, and real-time patient management.
Discussion: AI offers substantial benefits for CHF management by enabling data-driven, individualized care. Nonetheless, challenges remain, including variability in data quality, lack of algorithm transparency, and ethical considerations regarding patient privacy and accountability.
Conclusion: AI holds transformative potential for CHF management. Its successful integration can enhance diagnostic precision, personalize treatment, and support proactive patient care- ultimately improving outcomes and reducing the global burden of CHF.
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