Prof. Hans-Peter Brunner-La Rocca Presents Cardio Explorer® at ESC Munich
Originally published on explorishealth.com
24 min · Digital Health Symposium, ESC Congress 2026, Munich
Presented at the Digital Health Symposium at ESC in Munich, highlighting the potential of multi-marker AI to improve the assessment of obstructive coronary artery disease and patient selection for downstream testing.
The exclusion of acute coronary syndrome does not exclude underlying coronary artery disease. Yet 70–80% of patients presenting to Chest Pain Units are troponin-negative, leaving an important clinical question unresolved: who is actually at risk of obstructive CAD?
Current ESC Risk Factor-Weighted Clinical Likelihood assessment has important limitations. Based on a limited number of clinical parameters and strongly influenced by symptom classification, it may underestimate risk in atypical presentations while directing many intermediate-risk patients towards CCTA.
Cardio Explorer® takes a multi-marker AI approach, combining 32 routinely available clinical parameters to capture complex, non-linear relationships associated with obstructive CAD. In the presented validation, the model achieved an AUC of 0.878.
Importantly, the potential value extends beyond diagnostic prediction. The presented analysis showed that Cardio Explorer® can distribute patients more selectively across diagnostic probability thresholds, potentially supporting more targeted use of CCTA, functional testing and invasive angiography.
The key message from ESC Munich: the next step for cardiovascular AI is not simply better prediction, but translating more individualized risk assessment into better clinical decisions and more efficient care pathways — improving overall hospital economics.
Interested in how Cardio Explorer® applies to your coronary pathway? Our team is happy to walk you through the platform and the evidence behind it.
