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•स्क्रिनमा देखिने चुरोट: सुर्तीजन्य हानि न्यूनीकरण नीतिमा दक्षिण एसियाले अझै के छुटाइरहेको छ•नेपालमा पिसाब नलीको संक्रमण र एन्टिबायोटिक प्रतिरोधको बढ्दो संकट•Frontline Perspectives on Nursing Leadership in Nepal•Protecting the Smallest Lungs from the Hidden Grip of RSV in Kathmandu•The Heavy Burden of Bullying on Student Wellbeing in Nepal•The Emerging Landscape of Thyroid Health in Central Nepal•How a Recent Western Nepal Study is Redefining Anemia Diagnosis•How H. Pylori is Impacting the Health of Karnali’s High-Altitude Communities•Sweet Poison, Bitter Reality: The Unseen Diabetes Epidemic Among Nepal’s Youth•How Missing Checklists and Protocols are Costing Lives in Nepal’s ERs•स्क्रिनमा देखिने चुरोट: सुर्तीजन्य हानि न्यूनीकरण नीतिमा दक्षिण एसियाले अझै के छुटाइरहेको छ•नेपालमा पिसाब नलीको संक्रमण र एन्टिबायोटिक प्रतिरोधको बढ्दो संकट•Frontline Perspectives on Nursing Leadership in Nepal•Protecting the Smallest Lungs from the Hidden Grip of RSV in Kathmandu•The Heavy Burden of Bullying on Student Wellbeing in Nepal•The Emerging Landscape of Thyroid Health in Central Nepal•How a Recent Western Nepal Study is Redefining Anemia Diagnosis•How H. Pylori is Impacting the Health of Karnali’s High-Altitude Communities•Sweet Poison, Bitter Reality: The Unseen Diabetes Epidemic Among Nepal’s Youth•How Missing Checklists and Protocols are Costing Lives in Nepal’s ERs

Artificial Intelligence in Heart Failure: From Earlier Disease Detection to Integrated Care Delivery.

Researchers

Eduardo Pérez-Guerrero, Shyon Parsa, Ahmed A Eltahir, Matthew W Segar, Evangelos K Oikonomou, Richard K Cheng, Alex T Sandhu, Ambarish Pandey, David Ouyang, Timothy J Poterucha, Faraz S Ahmad, Rohan Khera, Pierre Elias, Marco V Perez, Euan A Ashley, Sneha S Jain

Abstract

Artificial intelligence (AI) is increasingly positioned to improve heart failure (HF) care by predicting risk, enabling earlier disease identification, and supporting more reliable delivery of evidence-based management. Current applications span opportunistic detection for low ejection fraction, HF with preserved ejection fraction, and structural heart disease using tools such as AI-enabled electrocardiography, imaging- and electronic health record‒based risk stratification, clinician-facing decision support, remote medication titration, and wearable monitoring platforms. The strongest evidence suggests that AI is most effective when embedded into active clinical workflows that guide targeted testing, treatment optimization, and longitudinal follow-up, rather than functioning as passive alerts alone. This review examines the emerging landscape of AI-enabled HF care delivery from early detection through chronic management, with emphasis on implementation, workflow integration, and the capacity of these tools to improve diagnostic yield and ultimately scalability.
Source: PubMed (PMID: 43009252)View Original on PubMed