Editorial: Contemporary applications of machine learning and artificial intelligence for the management of heart failure.

Abstract

Heart failure (HF) is a complex syndrome with substantial clinical and economic impact. This editorial highlights four original articles published in Frontiers in Cardiovascular Medicine that showcase contemporary applications of machine learning and artificial intelligence (AI) in HF management. These studies address early diagnosis through novel biomarkers, disease stratification based on transcriptomics, mechanistic insight into apoptotic pathways, and predictive telemonitoring using real-time AI models. Collectively, these contributions exemplify the transformative potential of data-driven technologies in personalizing care and preventing decompensation in HF. We discuss both the promise and challenges of integrating these tools into routine.