Thousands of cardiac digital twins give new insight into conduction and repolarisation

Shuang Qian and colleagues built a population of cardiac digital twins with machine learning, and published the results in Nature Cardiovascular Research.

The group built digital twins at a scale that had not been attempted before, using machine learning to make personalisation tractable across a population rather than one patient at a time. The work gives new insight into how conduction and repolarisation vary between people.

Published in Nature Cardiovascular Research, doi.org/10.1038/s44161-025-00650-0.