Everyone with an interest in AI, ECGs, or cardiology should read our paper out in Nature Medicine today! The DRAI MARTINI study tested the performance of DeepRhythmAI from
#MEDICALgorithmics for direct-to-physician reporting of ambulatory ECGs. The results overwhelmingly favour the AI, with 14 times fewer missed diagnoses of critical arrhytmias.
Read it here:
nature.com/articles/s41591-0…
Here's the study in brief:
🏥 >200,000 days of ECGs from >14,000 patients
🩺 >50 experts provided 3-cardiologist beat-to-beat consensus panel annotations of >5,000 ECG events
🖥️ Innovative study design provides absolute rates of missed diagnoses of AF or SVT ≥30s, 3rd degree block, 3.5s asystole or >10s VT
Results:
🫀Missed diagnoses in 3.2/1000 patients by DeepRhythm and 44.3/1000 patients by techs
🫀Superior sensitivity (98.6% vs 80.3%)
🫀NPV >99.9% for DeepRhythmAI.
This study is the result of an awesome collaboration with true leaders in the field who not only gave their scientific expertise but also committed many hours of their own time doing beat-to-beat annotations of >5,300 ECG events, with consensus annotation on every single beat. This resulted in an impressive author list including
@EmmaSvennberg @SZDiederichsen @DrJasonAndrade @WFMMD @AlexanderPBenz @EPjeff17 @PlatonovPyotr @StavrosStavrak1 @Cardiaficionado @Dominik_Linz @JuanBenezet @PhilippKrisai @SanjeevBhavnani @AlirezaOraii @ManningerMartin and many more!