The Role of Artificial Intelligence in Exercise-Based Cardiovascular Health Interventions: A Scoping Review

Background: As cardiovascular medicine advances rapidly, the integration of artificial intelligence (AI) has garnered increasing attention. Despite its growing application across various domains, the role of AI in exercise-based interventions remains relatively underexplored, offering a novel and promising direction for future research. Objective: This scoping review aimed to identify and analyse original studies that have applied AI to exercise-based interventions designed to improve cardiovascular outcomes. Methods: Following the PRISMA-ScR guidelines, PubMed, Scopus, Web of Science, Embase, and IEEE Xplore were searched for articles published between January 2015 and August 2025. Eligible studies were peer-reviewed human research employing AI (machine learning or deep learning) to deliver, adapt, or monitor an exercise intervention with cardiovascular outcomes. Reviews, diagnostic-only studies, protocols without data, and animal studies were excluded. Data extraction focused on study design, AI method, exercise modality, outcomes, and findings. Results: From 2,183 records, 11 studies met the inclusion criteria. Designs included feasibility pilots, randomized controlled trials (RCTs), and validation studies. AI applications encompassed adaptive step goals, reinforcement learning for engagement, coaching apps, machine learning–based exercise prescription, and continuous monitoring (e.g., VO₂ estimation). These AI methods, such as machine learning and reinforcement learning, were used to personalize exercise interventions and improve cardiovascular outcomes. Reported outcomes included blood pressure reduction, improved adherence, increased daily steps, improvement in VO₂max, continuous physiological monitoring, and enhanced diagnostic accuracy. Conclusions: Although evidence remains limited, findings demonstrate AI’s potential to personal exercise interventions, enable continuous monitoring, and enhance adherence in cardiovascular care. These findings suggest that AI could be a valuable tool in the development of more effective and personalized exercise-based interventions. However, large-scale RCTs, methodological standardization, and explainable AI approaches are urgently needed to ensure reliability, equity, and clinical translation. These future research directions are crucial for the successful integration of AI in cardiovascular care.