• Increased depth of analysis (80+ detection classes, ST, HRV, etc.)
• 24/7 online access to ECG data for doctors
• Ability to process cardiac data from any type of ECG device *
• Complete, clinician-ready analysis report based on the patient’s ECG data.
• The speed and accuracy of ECG annotation and interpretation is one of the best on the market
• Localization in Ukrainian/English languages

* Wellness devices e.g. AppleWatch, SmartWatches, and ECG Cardiographs are not supported. Already validated: Bittium, Cortium, LifeSignals, Livetec, BTL, ScottCare Holter, Amedtec, Phillips.

What can detect:

General:

• Automatism (Bradycardia, Tachycardia, СА Block (II, III), Asystole)
• Excitability (Rhythm: Sinus, Atrial, Nodal, Ventricular)
• Conductivity (AV Block (I, II, III), AV Dissociation, Intraventricular Block)
• Pre-excitation (Wolf-Parkinson-White syndrome, Lown-Ganong-Levine syndrome)

Ectopia: Supraventricular, Ventricular, Tachycardia, Fibrillation/Flatter

PQRST: PQ int/segment, QT (QTc), QRS, ST abnormalities

• For Physicians and attending Clinicians all the above transforms into high-quality reports that frequently contain references to the strips that would be otherwise hard or even impossible to spot with conventional Holter processing pipelines.
• The software resides completely in the cloud, leading to another strong point – the ability of doctors to access the evidence online, from anywhere.
• The report becomes clickable for all the statistics and strips, leading to the signal in context.
• This allows for any depth of exploration, particularly for patients with multiple arrhythmia types. It opens the internals of the record to the attending clinician, helping to build trust between the doctor and a diagnostic center.

• AI’s classification ability sets the quality standard, supporting clinics and healthcare providers with high-quality assessment output.
• The Cardio.AI platform already understands almost any possible arrhythmia or conduction issue, and the team is constantly working towards reaching full coverage, including even rare arrhythmias, achieving a state of clinical excellence in ECG interpretation.
• The process of improving the AI is conceptually very simple: the team continuously adds challenging data strips to the training pipeline, eventually ensuring the quality converges to be above 90% on any particular arrhythmia class, with some classes, like Atrial Fibrillation or Ventricular ectopic rhythms, consistently performing above 98%. This high level of consistent performance is what enables the specialist to focus on validation, not manual counting.