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.
Francisco Epelde (Fri,) studied this question.