ARTICLE SUMMARY:
After developing algorithms to make it easier for clinicians to review echocardiogram data from routine heart monitoring, the founders of AccurKardia found they were able to apply AI to the ECG to identify aortic stenosis much earlier than it is typically diagnosed.
AccurKardia is using AI to mine the information contained in widely available 12-lead ECG data. The start-up’s mission is to increase early access to cardiovascular screening with a cost-effective and easy-to-use tool. It’s too often the case that by the time patients present with noticeable symptoms, the disease has progressed and is more difficult to treat.
The company was founded in 2019 by CEO Juan C. Jimenez; Mohamed Sadeq Ali, chief operating officer; Tony Kuttiachen, general manager of cardiac monitoring; Naveen Srinivas, now a senior adviser; and John Fox, senior adviser. At the time, its goal was to create device-agnostic software to improve the interpretation of ECGs collected by traditional devices—Holter monitors, event recorders, cardiac patches, and mobile cardiac telemetry—to help clinicians arrive at diagnoses more quickly, reliably, cost effectively, and equitably among different geographies. CEO Jimenez says, “When my co-founders and I decided to join forces, I was shocked that in the 21st century, people were still using calipers to review electrocardiogram data.” Interpreting ECGs is often still a highly manual task, he notes, and many critical conditions are missed.
