Cardiac arrhythmia is an early symptom of many diseases: Paul Egan and his team aim to interpret the disturbance patterns.
Reading an electrocardiogram (ECG) is one of the standard tasks of a medical doctor. Why do we need CardioAI, Mr Egan?
We have extended the diagnostic abilities of an ECG. Even diseases like cancer or diabetes leave their mark on the heart rhythm; this already happens at an early stage. But so far, it has not been possible to detect these traces. We want to change that. The basic idea comes from my partner Andrey Ignatov, a machine learning PhD student I met on the Business Concept course.
What’s your approach?
We have developed deep-learning algorithms that recognize patterns in ECG waveforms. If these patterns are significant for certain diseases, they could be used for early diagnosis.
For a startup, it is not easy to get solid medical data…
We do indeed need a lot of patient data to validate our disturbance patterns. That is why my second partner Ivan Anastasi has been leading discussions for future cooperation with hospitals such as Insel-Spital Bern.
Your business model is based on partnerships with hospitals and doctors but may also include the sale of wearables. Who will wear these gadgets?
Anyone who values their health; especially, of course, people who belong to high-risk groups because they smoke, for example.
Where are you going next?
We are working on a convincing business plan. This will help us in our search for potential sponsors.