Detecting occlusive myocardial infarction using the electrocardiogram

Predicting occlusive myocardial infarction using deep learning based algorithms for the electrocardiogram

In a groundbreaking collaboration, we have established a public-private partnership at UMC Utrecht with Cordys Analytics to revolutionize the diagnosis of occlusion myocardial infarction (OMI). Using Artificial Intelligence (AI) powered electrocardiogram (ECG) analysis, our project aims to reshape the landscape of cardiac care.

Coronary heart disease remains a leading global health challenge, with timely diagnosis playing a pivotal role in improving patient outcomes. At the heart of our initiative is the recognition that traditional screening methods, particularly the electrocardiogram, face limitations in terms of sensitivity and specificity for detecting OMI. By harnessing the potential of AI-driven ECG analysis, we are developing a sophisticated algorithm capable of identifying patients with OMI. This approach not only streamlines the diagnostic process but also identifies cases where quick transfer to a cardiac intervention is beneficial, optimizing resource allocation and increasing efficiency. The societal impact of our project is vast as it will improve workflow and decrease the need for downstream diagnostics.

Our approach involves the integration of ECG datasets from multiple hospitals, providing a robust foundation for the development of the AI algorithm. Rigorous validation within the UMC Utrecht and other organizations ensures the algorithm's accuracy and reliability in real-world medical settings. This initiative not only contributes to the advancement of medical technology but also sets a new standard for the efficient and accurate diagnosis of OMI.

As we near the completion of our project, the anticipated deliverables include a refined AI algorithm and a comprehensive validation report. Our end goal is to redefine OMI diagnosis and management, ultimately leading to improved patient outcomes and an enhanced quality of life for individuals affected by OMI. Join us in a new era of cardiac care that combines cutting-edge technology with a commitment to bettering the lives of those facing heart-related challenges.

Summary
Transforming the chest pain care pathway by employing AI in electrocardiogram analysis, streamlining workflows, optimizing resources, and improving patient care and outcomes.
Technology Readiness Level (TRL)
2 - 7
Time period
36 months
Partners
UMC Utrecht logo
Cordys Analytics logo