Home > Cardiology > EHRA 2022 > Diagnostics and Prevention > AI model accurately discriminates between arrhythmias

AI model accurately discriminates between arrhythmias

Presented By
Dr Arunashis Sau, Imperial College London, UK
Presented by
Arunashis Sau Imperial College London
Conference
EHRA 2022
Doi
https://doi.org/10.55788/84de9f2e
An artificial intelligence (AI) model was able to successfully distinguish between patients with mus (CTI)-dependent atrial flutter and non-CTI dependent atrial tachycardia, based on patient ECGs. Since the model performed well in this proof-of-concept study, future studies will explore the diagnostic capacities of AI with regard to other arrhythmias. It would be helpful for clinicians and patients if the mechanism of arrhythmias could be identified via ECGs with a high degree of certainty, according to Dr Arunashis Sau (Imperial College London, UK) [1]. Two main categories of atrial arrhythmias are CTI-dependent atrial flutter and non-CTI dependent atrial tachycardia. The current study aimed to train a convolutional neural network to discriminate between these 2 categories of arrhythmias. The model was compared with expert assessments, using an invasive electrophysiology study as the source of truth. Collected were 13,557 ECGs from 288 patients. The train...


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