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About PMcardio-edu: ECG analysis

PMcardio-edu is an AI-powered educational and reference tool that provides you with an opportunity to educate and train yourself on ECG interpretation. You will learn and get to know the latest guideline-driven patient management options. Our sophisticated AI is trained on early cardiovascular disease detection and supports you in your training and learning activities by working through sample cases with the assistance of our tool.

PMcardio-edu is the perfect tool to train yourself in ECG interpretation and to play through corresponding case studies with our AI. Simply take a photo of a training or textbook ECG on your phone and within 4 seconds PMcardio-edu provides you with an accurate analysis of the ECG and highlights the latest patient management options based on the most recent CVD guidelines and experts recommendations.

The results are based on the interpretation of over 10 million ECGs and were cross-validated by some of the world’s top cardiologists.


- Take a photo of the training or textbook ECG on your phone – Paper? Screen? Weak camera? PMcardio-edu doesn’t care. Powered by our sophisticated algorithms and powerful neural networks, we can digitize even the lowest quality ECGs. From any 12-lead ECG device!

- AI Interpretation – Using Machine Learning algorithms, PMcardio-edu will search its library and can educate you on up to 60 different cardiac pathologies.

- Learn about modern patient management options – Using the European Society of Cardiology guidelines and experts’ opinions, PMcardio-edu will ask you 4-5 questions and teach you the ideal course of action for the cardiac scenario under consideration.

- Share & Collaborate - Share your sample reports simply and securely within the platform with peers and specialists to collaborate, discuss and learn from case studies together.

CAUTION: PMcardio-edu is not a medical device and is intended to be used as an educational and reference tool only! The application must not be used in a clinical environment and must not be used for clinical decision-making.

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