The Narrative Review: Advancements in Heart Failure Diagnosis and Management using Artificial Intelligence: A New Era of Patient Care

Brar S.S.; Yathindra M.R.; Arias Arango J.S.; Gutierrez E.A.; Aldoohan F.; Chahal P.S.; Youssef A.; Narra M.S.; Tatineni M.B.; Saldaña J.M.A.; Torres G.R.; Shekhawat P.; Dave V. · Current Cardiology Reviews (2026) · DOI: 10.2174/011573403x369978250818060357

Resumen

Heart Failure (HF) is a prevalent medical illness worldwide that affects millions and is a substantial economic burden. Its epidemiological impact is on the rise due to factors such as the ageing of the population, increasing rates of diabetes and hypertension, and better survival post-myocardial infarction. Some limitations in HF management include diagnostic challenges, sudden progression of the disease, and rising rates of readmission. Continuous monitoring and limited therapeutic interventions add further complexity to care. Artificial Intelligence(AI) is essential in health care and has provided solutions for improving HF management. Techniques like machine learning and deep learning enhance clinical decision-making and patient care. AI helps physicians diagnose HF more precisely through the analysis of imaging and electrocardiograms. Additionally, the patients' risk is calculated using various AI algorithms to develop personalized treatments for each individual. AI will help healthcare providers identify problems early and select appropriate therapies, leading to better outcomes. Further areas for improvement include enhanced data integration, predictive accuracy, patient engagement, data privacy and ethics, as well as integration with clinical workflows. AI technologies will continue to evolve in managing and treating HF; ongoing exploration and development are crucial for its optimization. This review outlines the current progress and potential of AI in the future to ensure better patient care and healthcare practices. 2026, Bentham Science Publishers

Instituciones: Universidad Peruana de Ciencias Aplicadas