DRAI MARTINI

In this study, led by Dr Linda S. Johnson, Associate Professor at Lund University, Sweden, and Dr Jeffrey S. Healey, Professor of Cardiology at McMaster University, Canada, DeepRhythmAI (DRAI) outperformed human technicians in diagnosing cardiac arrhythmias.

Dive into DRAI

0 times lower risk of missed diagnosis

DRAI detects more arrhythmias than human technicians, raising the standards for ambulatory ECG analysis

0 patients

The world's largest study of AI for cardiac arrhythmia diagnosis.

0+ independent cardiologists

DeepRhythmAI and technicians were compared to diagnoses by panels of ≥50 independent cardiologists from world-leading institutions.

Explore the Research behind DRAI

Read the original DeepRhythmAI for autonoMous Analysis of RhyThm INvestigatIon (DRAI MARTINI) study

Read Nature Publication

Behind the paper by Linda S Johnson, Alexandra Måneheim, Alexander Benz, and Jeffrey S Healey

Read the Blog Post

Read what the experts are saying about DRAI MARTINI study

Discover the insights

Featured Resources

AI in ECG & Cardiac Risk – This Week in Cardiology

Dr John Mandrola discusses the use of AI in ECG analysis, cerebral embolisms following LAAC, and new approaches to anticoagulation therapy and their implications for clinical practice.

Listen on Medscape

AI-ready Healthcare – Linda Johnson: Clinical validation of ECG AI

Artificial intelligence for direct-to-physician reporting of ambulatory electrocardiography. Linda Johnson is an associate professor on cardiovascular research at the Lund university, Sweden.

Listen on Spotify

Technology at the
Service of Cardiology

The Future of Diagnosis is Here

DeepRhythmAI is a Polish innovation that is revolutionizing cardiac arrhythmia diagnostics. Designed with patients and doctors in mind, DeepRhythmAI analyses ambulatory ECGs tirelessly and with exceptional attention to detail. Thanks to DeepRhythmAI, physicians can speed up the time it takes to diagnose their patients.

AI Performance Proven by Independent Research

The DRAI MARTINI study included >14,600 patients. The results were presented in a late-breaking session at the ESC Congress 2024 in London and show that DRAI surpasses the current standard of care, where human technicians analyze the ECG. DRAI working on its own led to a 14 times lower risk of missed diagnosis of critical arrhythmias, including atrial fibrillation, ventricular tachycardia, supraventricular tachycardia, 3rd-degree AV-block, and asystoles, compared to ECG technicians.

The study was conducted by an international team of cardiologists from leading research centers, such as McMaster University, Lund University, the University of British Columbia, the Karolinska Institute, the University of Oklahoma, Hackensack University, and Copenhagen University.

Scientifically proven
efficiency

Outperformance of human technicians

The study demonstrated that our AI algorithm network (DRAI) outperforms human technicians in detecting heart rhythm disorders. This groundbreaking research marks a significant step in diagnosing and treating cardiovascular conditions.

Patient safety

In the DRAI MARTINI study, DRAI had a 14-times lower risk of missing critical cardiac arrhythmias compared to human technicians, guaranteeing greater patient safety.

Rigorously evaluated

The DRAI MARTINI study involved 50+ independent cardiologists from leading institutions worldwide. The results, which demonstrate the excellence of our cutting-edge technology, are based on analysis of more than 200,000 days of ECG from >14,000 patients.