The manual process of routine ECG interpretation is very expensive, time-consuming, and needs high qualifications. It doesn’t allow to serve more patients remotely and in clinics.

Problems of traditional ECG analysis:

  - ECG software is device-specific,
  - Waveforms are not easily interpretable,
  - Expertise is expensive, labor-intensive,
  - Even experts do sometimes miss important events.

Cardio.AI is a drop-in replacement for any Holter software on the market, works in browser (not a desktop application), uses AI to pass over data before the ECG technician kicks in, so the human only validates and corrects the mistakes (if any) instead of manual markup as it is done in today's solutions.

We are going to be a complete drop-in replacement for technical jobs in ECG processing, whatever short or long records we are processing. It's different from most screening algorithms out there because you need much higher events coverage, like 90-100 HL7 classes with accuracy 90%+, and you need a lot of other stuff, like morphology and ST-analysis, de-noising, accept any leads combinations, being able to generate the human-readable summarization of the report, etc

Share this project:

Updates