ENSIGHT-AI is transforming cardiovascular diagnostics through technology that can identify structural heart disorders from widely available electrocardiograms (ECGs) and wearables. Currently, expensive cardiac imaging is the only way to diagnose many structural heart diseases, so a majority of individuals remain undiagnosed until they develop symptoms. This often means more advanced and less treatable disease at diagnosis. In addition to the dire clinical need for a solution that allows easier and more accessible diagnostics, there is a large commercial need for such technology. Pharmaceutical companies developing therapeutics are challenged by slow trial enrollment and fewer than expected patients on therapies due to the reliance on advanced diagnostic imaging for identifying eligible patients.

ENSIGHT-AI fills this critical need by technology that can enhance the information we can get from ECGs being done in clinical settings globally for decades and is a low-cost and widely available data stream. With wearables, ECGs are becoming an increasingly common health information stream even outside the health setting. Typically, ECGs are available as PDFs or images that doctors review and make determinations on rhythm and conduction disorders. Our technology can take these images and identify signatures of structural heart disorders using novel and proprietary deep-learning algorithms.

The science was developed at Yale’s Cardiovascular Data Science (CarDS) Lab, and has won several awards and grants, including those from American Heart Association, Doris Duke Charitable Foundation, and Bristol Myers Squibb. ENSIGHT-AI is working to develop these technologies and is working towards regulatory submissions and has been awarded the Blavatnik Foundation Award and the Wilson Prize at Yale.