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Big Data and Trustworthy AI for Heart Failure: A Review
Joan Perramon-Llussà1, Grzegorz Skorupko1, Shishir Rao2
1Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Spain (J.P.-L., G.S., E.R.P., S.J.E.K., I.S., K.L., P.G.).
Circulation. Heart Failure
|May 11, 2026
Summary
Machine learning (ML) and artificial intelligence (AI) are transforming heart failure research by analyzing diverse data for diagnosis and treatment. Addressing challenges like data bias and privacy is crucial for effective clinical integration.
Area of Science:
- Cardiology
- Biomedical Informatics
- Artificial Intelligence
Background:
- Machine learning (ML) and artificial intelligence (AI) are rapidly advancing, fueled by large datasets.
- These technologies hold significant potential to revolutionize heart failure (HF) research and clinical practice.
Purpose of the Study:
- To provide an overview of ML/AI concepts in HF research.
- To examine the application of diverse data modalities for HF diagnosis, prognosis, risk stratification, and personalized treatment.
- To identify barriers to clinical translation and explore solutions for equitable and explainable AI.
Main Methods:
- Review of ML/AI concepts and applications in heart failure.
- Analysis of diverse data sources: EHRs, registries, biobanks, imaging, telemonitoring, synthetic data.
- Evaluation of strategies for addressing data heterogeneity, bias, privacy, and interoperability.
Main Results:
- ML/AI applications are being developed for HF diagnosis, prognosis, risk stratification, and personalized treatments using various data types.
- Key barriers include data heterogeneity, algorithmic bias, lack of interoperability, and privacy concerns.
- Emerging solutions like Federated Learning and synthetic data generation aim to improve fairness and privacy.
Conclusions:
- Successful clinical integration requires addressing technical challenges and prioritizing human-centered design, stakeholder engagement, and regulatory readiness.
- Interdisciplinary collaboration is essential for the scalable, ethical, and effective implementation of AI in heart failure management.
- Future priorities include developing explainable, equitable, and privacy-preserving AI systems for heart failure care.
Related Concept Videos
01:27Heart Failure I: Introduction
Heart failure refers to a clinical syndrome caused by structural or functional cardiac disorders that prevent the heart from pumping an adequate amount of blood to meet the body's metabolic needs. This condition often arises from myocardial infarction or ischemia, leading to decreased cardiac output, reduced tissue perfusion, impaired gas exchange, fluid volume imbalance, and decreased functional ability.Heart failure can result from disruptions in the mechanisms that regulate cardiac output...
01:30Heart Failure IV: Classification and Diagnostic Evaluation
Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
01:22Heart Failure VI: Adjunct Therapies
Additional therapies for treating patients with heart failure (HF) may include procedural interventions, supplemental oxygen, the management of sleep disorders, and nutritional therapy.Procedural InterventionsImplantable Cardioverter-Defibrillator: For patients at risk of life-threatening arrhythmias due to severe left ventricular dysfunction, an Implantable Cardioverter-Defibrillator (ICD) can detect and terminate these arrhythmias, preventing sudden cardiac death and improving survival rates.
01:30Heart Failure V: Medical Management
Medical Management of Acute Decompensated Heart Failure (ADHF)The primary goals of therapy for patients hospitalized with acute decompensated heart failure (ADHF) include:Relieving symptomsOptimizing volume statusSupporting oxygenation and ventilationMaintaining cardiac output (CO) and end-organ perfusionIdentifying and addressing the cause of ADHFPreventing complicationsProviding patient education on factors precipitating HF exacerbationPlanning for dischargeOngoing monitoring and assessment...
01:29Heart Failure II: Pathophysiology
Systolic Heart Failure and Compensatory MechanismsSystolic heart failure (also termed HFrEF, Heart Failure with Reduced Ejection Fraction) is the most prevalent type of heart filure. It results in a decreased volume of blood being pumped from the ventricle. The aortic arch and carotid sinuses have baroreceptors that detect reduced blood pressure, triggering the sympathetic nervous system (SNS) to release epinephrine and norepinephrine. Initially, this response aims to boost heart rate and...
01:29Cardiomyopathy V: Interprofessional Care
Managing cardiomyopathy involves addressing underlying or precipitating causes, treating heart failure with medications, and implementing dietary changes and a balanced exercise and rest regimen.Lifestyle ModificationsCardiomyopathy patients should adopt a low-sodium diet to reduce fluid retention and manage heart failure. A personalized exercise and rest plan helps maintain physical fitness without overstraining the heart. Avoiding alcohol and tobacco is essential to prevent further damage to...