Artificial intelligence in pediatric electrocardiography: Embracing the next decade of innovation
In medicine, every decade brings new tools and methods that reshape how we diagnose and treat disease. Right now, I see artificial intelligence (AI) emerging as that transformative force — especially in the realm of pediatric electrocardiography (ECG). In my recent work, I have been fortunate to witness firsthand how AI is helping healthcare providers see subtle patterns in pediatric ECGs that traditional analysis often misses. My colleagues and I summarized some of these breakthroughs in our recent review which finds that AI is not an abstract concept, but rather a powerful tool pushing the boundaries of what we can do in clinical practice.
AI offers unprecedented insights: advanced models can detect not just right or left ventricular dysfunction from a simple ECG, but also they have the uncanny ability to predict sex differences in cardiac signals using sophisticated pattern recognition, as shown in this study. These capabilities far exceed what humans are able to accomplish through traditional visual analysis alone. It amazes me how, with just a few seconds of digital data, AI can highlight early cardiac changes which gives healthcare providers a chance to intervene sooner and more effectively.
Looking ahead, the next decade will likely unleash a wave of predictive and diagnostic innovations powered by AI. Imagine reliable algorithms that instantly analyze ECGs to forecast outcomes, identify risks and send alerts on emergent issues. One promising area is multimodal AI where ECG data merges with imaging, lab results and other clinical variables into more effective models. Far from diminishing the clinician’s role, AI stands to amplify our skills, giving doctors a clearer roadmap for managing a patient’s heart health. 
But this promise brings responsibility. To harness AI effectively, we need to stay informed, remain critical and adopt a measured approach. AI is not a magical solution; it is a tool that can elevate our practice if used thoughtfully. We also must be prepared to explain its outputs, ensure its ethical use and maintain oversight to guard against bias or misuse.
As AI revolutionizes pediatric and adult congenital heart disease care, we are witnessing a shift in how research and data-sharing drives innovation. Multi-Institutional collaborations are uncovering novel insights, enabling more precise risk stratification and earlier detection of disease progression. Parents and patients overwhelmingly support research that improves outcomes, but trust in AI-driven tools depends on transparency, robust privacy protections and responsible data stewardship. Ensuring that these technologies are developed with ethical rigor will be key to sustaining public confidence and maximizing their impact.
At the same time, expanding equitable access to AI-driven advancements is paramount. AI has the potential to democratize specialized cardiac care, but only if it is deployed in a way that reaches all patients — including those in under-resourced hospitals and underserved communities. Public–private partnerships, innovative funding models and strategic policymaking can help bridge these gaps, ensuring that AI-driven diagnostics and decision-support tools benefit every child, not only those at well-funded institutions. By fostering a collaborative approach to AI integration, we can drive progress that transforms congenital heart disease care across the lifespan.
If you’re eager to track how rapidly cardiology, technology and AI are evolving, I invite you to join our new @CardioTechx journal club on X. By combining AI with the clinical acumen of physicians and researchers, we can push medicine to places we never thought possible, ultimately improving the lives of patients and families with structural heart disease around the globe.
By Dr. Donnchadh O’Sullivan, pediatric cardiology fellow at Baylor College of Medicine
