New AI Tool Flags Hidden Risk of Sudden Cardiac Death

Researchers in the Trayanova Lab at Johns Hopkins University, led by ADVANCE member Dr. Natalia Trayanova, as well as ADVANCE members from the Johns Hopkins School of Medicine and other collaborators, have developed a new AI tool that significantly improves prediction of sudden cardiac death in patients with hypertrophic cardiomyopathy. The tool, MAARS (Multimodal AI for Arrhythmic Risk Stratification), combines contrast-enhanced cardiac MRI with electronic health records to detect hidden scar patterns linked to fatal arrhythmias. In clinical testing, MAARS achieved 89% accuracy overall and 93% for patients aged 40–60, outperforming current risk assessment methods.

In this work, published in Nature Cardiovascular Research, MAARS not only identifies patients at high risk but also explains the underlying factors contributing to that risk, enabling more personalized and effective treatment decisions. The team is now extending the tool to other cardiac conditions, with further clinical trials underway.

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