Dublin’s Mater Hospital Launches AI Hub to Transform Patient Care and Speed Up Heart Attack Diagnosis

Dublin’s Mater Hospital Launches AI Hub to Improve Patient Care

The Mater Misericordiae University Hospital in Dublin has established the Centre for AI and Digital Health to develop artificial intelligence solutions aimed at improving patient care and speeding up clinical processes. Based at the Pillar Centre for Transformative Healthcare, this new hub will manage the introduction of AI tools within the hospital and facilitate collaborative research across departments.

AI in Cardiology: Faster Heart Attack Diagnosis

The hospital’s cardiology team is preparing to introduce an AI tool designed to assist in the rapid diagnosis of heart attacks, potentially accelerating treatment times. Currently, when patients present with chest pain, clinicians rely on electrocardiograms (ECGs) to detect ST segment elevation, a key indicator of blocked arteries leading to heart attacks. However, this marker appears in only 40-50% of such cases.

The AI tool aims to identify blocked arteries in approximately 90% of patients, effectively doubling the number of individuals who can receive prompt intervention. Early treatment is crucial, as reopening the blocked artery within 90 minutes reduces heart muscle damage and lowers mortality risk. While data on mortality reduction from this AI tool is still pending, experts believe it will likely improve patient outcomes.

Consultant cardiologist Prof Joe Galvin highlights that AI can detect subtle abnormalities in ECGs and cardiac ultrasounds that may be missed by the human eye. Another planned AI project focuses on assessing risks related to sudden arrhythmic death syndrome (SADS), providing valuable information for affected families.

Collaboration and Research at the AI Hub

Paul Banahan, senior AI research fellow at the Mater and Ireland’s first dedicated AI researcher in a clinical setting, emphasizes the importance of conducting AI research within the hospital environment. His work includes developing generative AI models that convert CT images into synthetic MRI images to improve emergency spinal care.

Banahan notes that the hospital setting enables complex, multidisciplinary projects that would be difficult or costly to carry out elsewhere. He is currently pursuing a PhD focused on generative AI models for brain imaging, aiming to forecast stroke progression and understand how AI interprets medical data.

Ethics and Safety in Healthcare AI

AI applications in healthcare raise important ethical and privacy issues, especially regarding sensitive patient data. The Mater Hospital follows strict research ethics and GDPR compliance. Every AI project undergoes a rigorous approval process by the hospital’s research ethics committee, ensuring clear documentation and safety measures.

Josephine Ryan Leacy, CEO of the Mater Hospital, stresses that the centre prioritizes patient safety, transparency, and delivering real clinical benefits. Prof Galvin adds that AI is an additional diagnostic aid that supports clinicians rather than replacing their judgment. The responsibility for patient care remains firmly with the clinician, who uses AI as a tool to enhance decision-making.

Further Learning and Resources

Healthcare professionals interested in understanding AI applications in clinical settings may find value in exploring targeted AI courses and certifications. Platforms like Complete AI Training offer resources tailored for healthcare roles, helping teams integrate AI tools effectively and safely.